Published Research Article That Uses Chi Square Test

Published Research Articles That Use the Chi-Square Test: A Comprehensive Guide

Are you a researcher looking to analyze categorical data? Or perhaps a student delving into the world of statistical analysis? Understanding and applying the chi-square test is crucial for countless research endeavors. This comprehensive guide dives deep into published research articles that effectively utilize the chi-square test, providing real-world examples and practical insights to help you understand its application, interpretation, and limitations. We’ll explore various types of chi-square tests, examine successful research studies that leverage this powerful statistical tool, and equip you with the knowledge to evaluate its use in academic literature. Prepare to unlock the secrets behind this fundamental statistical method and elevate your research capabilities.

Understanding the Chi-Square Test: A Foundation for Analysis

The chi-square (χ²) test is a non-parametric statistical test used to analyze categorical data. It determines if there’s a significant association between two categorical variables. In simpler terms, it helps researchers understand if the observed frequencies of events differ significantly from the expected frequencies. This difference, if significant, suggests a relationship between the variables under investigation. There are several variations of the chi-square test, each tailored to specific research questions:

Chi-Square Goodness-of-Fit Test: This test compares the observed distribution of a single categorical variable to an expected distribution. For example, a researcher might use this test to determine if the distribution of genders in a particular sample differs significantly from the expected 50/50 split.

Chi-Square Test of Independence: This test assesses whether two categorical variables are independent of each other. This is the most commonly used type of chi-square test in research. For example, a researcher might investigate whether there's a relationship between smoking status (smoker/non-smoker) and lung cancer diagnosis (yes/no).

Chi-Square Test of Homogeneity: This test compares the distribution of a single categorical variable across different populations or groups. For instance, a researcher might use this test to compare the distribution of political affiliations among different age groups.

The core principle behind all chi-square tests is the comparison of observed and expected frequencies. A significant chi-square statistic indicates a statistically significant difference between these frequencies, suggesting a relationship between the variables. The p-value associated with the chi-square statistic helps determine the significance level. A p-value less than the chosen significance level (typically 0.05) indicates a statistically significant relationship.

Published Research Examples Utilizing the Chi-Square Test

Let's examine a few examples of published research articles that effectively use the chi-square test:

Example 1: Analyzing the Relationship Between Diet and Disease

A study published in the Journal of the American Medical Association might investigate the relationship between dietary habits (high-fat diet vs. low-fat diet) and the incidence of cardiovascular disease. Researchers would collect data on dietary habits and disease status from a large sample and use the chi-square test of independence to determine if there's a statistically significant association between these two categorical variables. A significant result might indicate that individuals with a high-fat diet have a significantly higher incidence of cardiovascular disease compared to those with a low-fat diet.

Example 2: Exploring the Association Between Socioeconomic Status and Educational Attainment

A research article in the American Sociological Review could explore the association between socioeconomic status (high, middle, low) and educational attainment (high school diploma, bachelor's degree, postgraduate degree). Using the chi-square test of independence, researchers could analyze whether certain socioeconomic groups are more likely to achieve higher levels of education. Significant results would highlight potential inequalities in educational access and attainment.

Example 3: Examining the Effectiveness of a New Treatment

A clinical trial published in The Lancet might assess the effectiveness of a new drug treatment for a particular disease. Researchers could use the chi-square test of homogeneity to compare the success rates (cured/not cured) of the new treatment versus a placebo group. A significant result would suggest that the new treatment is more effective than the placebo.

Interpreting Results and Understanding Limitations

Interpreting chi-square results requires careful consideration. While a significant p-value indicates an association between variables, it doesn't imply causation. Correlation does not equal causation. Further analysis, such as calculating effect sizes (like Cramer's V), is often necessary to quantify the strength of the association. Additionally, it’s crucial to consider the limitations of the chi-square test. Small expected cell frequencies can lead to inaccurate results, necessitating techniques like Fisher's exact test for smaller datasets. The chi-square test also assumes independence of observations.

Case Study: A Detailed Analysis of a Published Research Article

Let's analyze a hypothetical published research article titled "The Impact of Social Media Use on Adolescent Mental Health."

Hypothetical Article Outline:

Introduction: Background on adolescent mental health and social media usage; research question and hypotheses; methodology overview.
Methods: Description of the study design (e.g., cross-sectional), sampling method, data collection tools (e.g., surveys), and statistical analysis techniques (chi-square test).
Results: Presentation of descriptive statistics, chi-square test results (including contingency tables, chi-square statistic, degrees of freedom, and p-value), and interpretation of findings.
Discussion: Interpretation of the results in the context of existing literature; limitations of the study; implications for future research; conclusions.
Conclusion: Summary of the key findings and their significance.

Detailed Explanation of Each Section:

The Introduction sets the stage, providing background information on the prevalence of mental health issues among adolescents and the growing concern about the impact of social media. The research question (e.g., Is there an association between excessive social media use and increased risk of depression or anxiety?) is clearly stated, along with testable hypotheses. The methodology is briefly outlined, giving the reader a roadmap of the study's design.

The Methods section provides a comprehensive description of the research design, the sampling strategy used to recruit participants, the instruments used to collect data (e.g., questionnaires assessing social media use and mental health symptoms), and the statistical analysis plan, specifically mentioning the use of the chi-square test to examine the association between social media use (categorized as low, moderate, high) and mental health status (e.g., diagnosed with depression/anxiety, no diagnosis).

The Results section presents the findings in a clear and concise manner, including contingency tables displaying the frequencies of social media use and mental health status. The chi-square test results are reported, including the chi-square statistic, degrees of freedom, p-value, and the interpretation of these findings. For instance, a significant p-value (e.g., p < 0.05) would suggest a statistically significant association between social media use and mental health status.

The Discussion section interprets the results in light of existing research, acknowledging any inconsistencies or supporting evidence. It carefully addresses the limitations of the study, such as potential confounding variables or the cross-sectional design's inability to establish causality. The section also discusses the implications of the findings for future research, suggesting potential areas for further investigation or methodological improvements. Finally, it summarizes the key conclusions, reinforcing the main findings.

The Conclusion summarizes the main findings and emphasizes their significance for understanding the relationship between social media use and adolescent mental health. It reiterates the implications of the findings and suggests avenues for future research to further explore this complex issue.

Frequently Asked Questions (FAQs)

1. What are the assumptions of the chi-square test? The chi-square test assumes that the data are categorical, observations are independent, and expected cell frequencies are sufficiently large (generally, at least 5).

2. What is the difference between a chi-square test of independence and a chi-square test of homogeneity? Both tests use the same statistical formula, but the research question differs. Independence tests whether two variables are related, while homogeneity tests whether the distribution of a single variable is the same across different groups.

3. What is a p-value, and how is it interpreted in the context of a chi-square test? A p-value represents the probability of observing the obtained results (or more extreme results) if there were no real association between the variables. A p-value below the significance level (typically 0.05) suggests a statistically significant association.

4. Can I use the chi-square test if I have small expected cell frequencies? No, small expected cell frequencies violate the assumptions of the chi-square test and can lead to inaccurate results. Fisher's exact test is a more appropriate alternative for small datasets.

5. How do I calculate the expected frequencies in a chi-square test? Expected frequencies are calculated based on the marginal totals of the contingency table. The formula is (row total column total) / grand total.

6. What are some effect size measures for the chi-square test? Cramer's V and phi coefficient are common effect size measures for the chi-square test, quantifying the strength of the association between the variables.

7. Can I use the chi-square test for ordinal data? While technically you can, it's not optimal. Ordinal data has an order (e.g., low, medium, high), which the chi-square test ignores. Consider other tests like the Cochran-Armitage trend test which accounts for the order.

8. What software can I use to perform a chi-square test? Many statistical software packages, including SPSS, R, SAS, and Stata, can perform chi-square tests.

9. How can I report the results of a chi-square test in a research paper? Report the chi-square statistic, degrees of freedom, p-value, and effect size (e.g., Cramer's V). Clearly describe the variables and the interpretation of the results in the context of your research question.

Related Articles

1. Interpreting Chi-Square Results: A Practical Guide: A detailed explanation of how to interpret chi-square statistics and p-values.

2. Choosing the Right Chi-Square Test: A Decision Tree: A guide to selecting the appropriate type of chi-square test for your research question.

3. Chi-Square Test vs. Fisher's Exact Test: When to Use Which: A comparison of the chi-square test and Fisher's exact test, highlighting their strengths and weaknesses.

4. Calculating Effect Size for Chi-Square Tests: A Step-by-Step Guide: A tutorial on calculating and interpreting effect sizes (like Cramer's V) for chi-square tests.

5. Common Mistakes in Using the Chi-Square Test: An overview of frequent errors made when applying the chi-square test and how to avoid them.

6. Advanced Applications of the Chi-Square Test: Exploration of more complex uses of the chi-square test, including analyzing multi-way contingency tables.

7. The Chi-Square Test in Medical Research: Examples and discussions of the use of chi-square in medical studies.

8. The Chi-Square Test in Social Science Research: Applications and interpretations of chi-square in social science contexts.

9. Power Analysis for Chi-Square Tests: Determining the sample size needed to detect a statistically significant effect using the chi-square test.


  published research article that uses chi square test: Goodness-of-Fit Tests and Model Validity C. Huber-Carol, N. Balakrishnan, M. Nikulin, M. Mesbah, 2012-12-06 The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.
  published research article that uses chi square test: Clinical Biostatistics Alvan R. Feinstein, 1977
  published research article that uses chi square test: A Guide to Chi-Squared Testing Priscilla E. Greenwood, Michael S. Nikulin, 1996-04-05 The first step-by-step guide to conducting successful Chi-squaredtests Chi-squared testing is one of the most commonly applied statisticaltechniques. It provides reliable answers for researchers in a widerange of fields, including engineering, manufacturing, finance,agriculture, and medicine. A Guide to Chi-Squared Testing brings readers up to date on recentinnovations and important material previously published only in theformer Soviet Union. Its clear, concise treatment and practicaladvice make this an ideal reference for all researchers andconsultants. Authors Priscilla E. Greenwood and Mikhail S. Nikulin demonstratethe application of these general purpose tests in a wide variety ofspecific settings. They also * Detail the various decisions to be made when applying Chi-squaredtests to real data, and the proper application of these tests instandard hypothesis-testing situations * Describe how Chi-squared type tests allow statisticians toconstruct a test statistic whose distribution is asymptoticallyChi-squared, and to compute power against various alternatives * Devote half of the book to examples of Chi-squared tests that canbe easily adapted to situations not covered in the book * Provide a self-contained, accessible treatment of themathematical requisites * Include an extensive bibliography and suggestions for furtherreading
  published research article that uses chi square test: Statistical Power Analysis for the Behavioral Sciences Jacob Cohen, 2013-05-13 Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of qualifying dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
  published research article that uses chi square test: Statistics on the Table Stephen M. Stigler, 2002-09-30 This lively collection of essays examines statistical ideas with an ironic eye for their essence and what their history can tell us for current disputes. The topics range from 17th-century medicine and the circulation of blood, to the cause of the Great Depression, to the determinations of the shape of the Earth and the speed of light.
  published research article that uses chi square test: Practical Statistics David Kremelberg, 2010-03-18 Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.
  published research article that uses chi square test: Econometric Advances in Spatial Modelling and Methodology Daniel A. Griffith, C. Amrhein, Jean-Marie Huriót, 2013-10-25 The purpose of models is not to fit the data but to sharpen the questions. S. Karlin, 11th R. A. Fisher Memorial Lecture, Royal Society, 20 April 1983 We are proud to offer this volume in honour of the remarkable career of the Father of Spatial Econometrics, Professor Jean Paelinck, presently of the Tinbergen Institute, Rotterdam. Not one to model solely for the sake of modelling, the above quotation nicely captures Professor Paelinck's unceasing quest for the best question for which an answer is needed. His FLEUR model has sharpened many spatial economics and spatial econometrics questions! Jean Paelinck, arguably, is the founder of modem spatial econometrics, penning the seminal introductory monograph on this topic, Spatial Econometrics, with Klaassen in 1979. In the General Address to the Dutch Statistical Association, on May 2, 1974, in Tilburg, he coined the term [spatial econometrics] to designate a growing body of the regional science literature that dealt primarily with estimation and testing problems encountered in the implementation of multiregional econometric models (Anselin, 1988, p. 7); he already had introduced this idea in his introductory report to the 1966 Annual Meeting of the Association de Science Regionale de Langue Fran~aise.
  published research article that uses chi square test: Data Analysis in Management with SPSS Software J.P. Verma, 2012-12-13 This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS. It strengthens the intuitive understanding of the material, thereby increasing the ability to successfully analyze data in the future. The book provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of research problems. This book focuses on providing readers with the knowledge and skills needed to carry out research in management, humanities, social and behavioural sciences by using SPSS.
  published research article that uses chi square test: Learning Statistics with R Daniel Navarro, 2013-01-13 Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
  published research article that uses chi square test: The Concise Encyclopedia of Statistics Yadolah Dodge, 2008-04-15 The Concise Encyclopedia of Statistics presents the essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the vast community using statistics in medicine, engineering, physical science, life science, social science, and business/economics. The reference is alphabetically arranged to provide quick access to the fundamental tools of statistical methodology and biographies of famous statisticians. The more than 500 entries include definitions, history, mathematical details, limitations, examples, references, and further readings. All entries include cross-references as well as the key citations. The back matter includes a timeline of statistical inventions. This reference will be an enduring resource for locating convenient overviews about this essential field of study.
  published research article that uses chi square test: OpenIntro Statistics David Diez, Christopher Barr, Mine Çetinkaya-Rundel, 2015-07-02 The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
  published research article that uses chi square test: Goodness-of-Fit-Techniques RalphB. D'Agostino, 2017-10-19 Conveniently grouping methods by techniques, such as chi-squared and empirical distributionfunction , and also collecting methods of testing for specific famous distributions, this usefulreference is the fust comprehensive.review of the extensive literature on the subject. It surveysthe leading methods of testing fit . .. provides tables to make the tests available . .. assessesthe comparative merits of different test procedures . .. and supplies numerical examples to aidin understanding these techniques.Goodness-of-Fit Techniques shows how to apply the techniques . .. emphasizes testing for thethree major distributions, normal, exponential, and uniform . .. discusses the handling of censoreddata .. . and contains over 650 bibliographic citations that cover the field.Illustrated with tables and drawings, this volume is an ideal reference for mathematical andapplied statisticians, and biostatisticians; professionals in applied science fields, including psychologists,biometricians , physicians, and quality control and reliability engineers; advancedundergraduate- and graduate-level courses on goodness-of-fit techniques; and professional seminarsand symposia on applied statistics, quality control, and reliability.
  published research article that uses chi square test: Psychological Statistics Using SPSS for Windows Robert C. Gardner, 2001 This unique text on psychological statistics 1) provides the general rationale underlying many statistical procedures commonly used in psychology, 2) covers a wide range of topics--from the logic of statistical inference to multivariate analysis of variance, and 3) gives simple step-by-step instructions on how to access the relevant SPSS program. Each chapter presents a different procedure (e.g., t-tests, factor analysis, etc.), and briefly describes the basic concepts, purpose, and history necessary to understanding its strengths and limitations. A concrete example is used for each procedure, with the discussion of the SPSS output being directly linked to the underlying statistical model, so that readers can see how the interpretation of results follows from the nature of that procedure. Chapter topics include statistics, computers, and statistical packages; the t-test; single factor analysis of variance designs; completely randomized factorial designs; single factor repeated measures designs; split plot analysis of variance; chi-square analysis of frequency data; bivariate regression and correlation; multiple regression and multiple correlation; factor analysis; and multivariate analysis of variance. A reference guide for statisticians--to remind them of procedures learned earlier in their careers.
  published research article that uses chi square test: Statistical Inference Ayanendranath Basu, Hiroyuki Shioya, Chanseok Park, 2011-06-22 In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by Minimum Distance Estimation is literally huge. Filling a statistical resource gap, Stati
  published research article that uses chi square test: Pediatric Board Study Guide Osama Naga, 2015-03-27 Covers the most frequently asked and tested points on the pediatric board exam. Each chapter offers a quick review of specific diseases and conditions clinicians need to know during the patient encounter. Easy-to-use and comprehensive, clinicians will find this guide to be the ideal final resource needed before taking the pediatric board exam.
  published research article that uses chi square test: Simulating chi-square data through algorithms in the presence of uncertainty Muhammad Aslam, Osama H. Arif , 2024-01-01 This paper presents a novel methodology aimed at generating chi-square variates within the framework of neutrosophic statistics. It introduces algorithms designed for the generation of neutrosophic random chi-square variates and illustrates the distribution of these variates across a spectrum of indeterminacy levels. The investigation delves into the influence of indeterminacy on random numbers, revealing a significant impact across various degrees of freedom. Notably, the analysis of random variate tables demonstrates a consistent decrease in neutrosophic random variates as the degree of indeterminacy escalates across all degrees of freedom values. These findings underscore the pronounced effect of uncertainty on chi-square data generation. The proposed algorithm offers a valuable tool for generating data under conditions of uncertainty, particularly in scenarios where capturing real data proves challenging. Furthermore, the data generated through this approach holds utility in goodness-of-fit tests and assessments of variance homogeneity.
  published research article that uses chi square test: Communication Research Statistics John C. Reinard, 2006-04-20 While most books on statistics seem to be written as though targeting other statistics professors, John Reinard′s Communication Research Statistics is especially impressive because it is clearly intended for the student reader, filled with unusually clear explanations and with illustrations on the use of SPSS. I enjoyed reading this lucid, student-friendly book and expect students will benefit enormously from its content and presentation. Well done! --John C. Pollock, The College of New Jersey Written in an accessible style using straightforward and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research undertaken in communication studies. This introductory textbook is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel XP. Key Features: Emphasizes basic and introductory statistical thinking: The basic needs of novice researchers and students are addressed, while underscoring the foundational elements of statistical analyses in research. Students learn how statistics are used to provide evidence for research arguments and how to evaluate such evidence for themselves. Prepares students to use statistics: Students are encouraged to use statistics as they encounter and evaluate quantitative research. The book details how statistics can be understood by developing actual skills to carry out rudimentary work. Examples are drawn from mass communication, speech communication, and communication disorders. Incorporates SPSS 12 and Excel: A distinguishing feature is the inclusion of coverage of data analysis by use of SPSS 12 and by Excel. Information on the use of major computer software is designed to let students use such tools immediately. Companion Web Site! A dedicated Web site includes a glossary, data sets, chapter summaries, additional readings, links to other useful sites, selected calculators for computation of related statistics, additional macros for selected statistics using Excel and SPSS, and extra chapters on multiple discriminant analysis and loglinear analysis. Intended Audience: Ideal for undergraduate and graduate courses in Communication Research Statistics or Methods; also relevant for many Research Methods courses across the social sciences
  published research article that uses chi square test: Pain Alaa Abd-Elsayed, 2019-05-10 This concise but comprehensive guide covers common procedures in pain management necessary for daily practice, and includes topics on international pain medicine curricula, for example, the American Board of Anesthesiology, World Institute of Pain/Fellow of Interventional Pain Practice, and American Board of Pain Medicine. Treatments for pain are discussed, including nerve blocks (head, neck, back, pelvis and lower extremity). Chapters have a consistent format including high yield points for exams, and questions in the form of case studies. Pain: A Review Guide is aimed at trainees in pain medicine all over the world. This book will also be beneficial to all practitioners who practice pain.
  published research article that uses chi square test: Biostatistics for Radiologists Francesco Sardanelli, Giovanni Di Leo, 2009-03-31 The aim of this book is to present statistical problems and methods in a friendly way to radiologists, emphasizing statistical issues and methods most frequently used in radiological studies (e.g., nonparametric tests, analysis of intra- and interobserver reproducibility, comparison of sensitivity and specificity among different imaging modality, difference between clinical and screening application of diagnostic tests, ect.). The tests will be presented starting from a radiological problem and all examples of statistical methods applications will be radiological.
  published research article that uses chi square test: Comparative Effectiveness Review Methods U. S. Department of Health and Human Services, Agency for Healthcare Research and Quality, 2013-05-17 The Agency for Healthcare Research and Quality (AHRQ) commissioned the RTI International–University of North Carolina at Chapel Hill (RTI-UNC) Evidence-based Practice Center (EPC) to explore how systematic review groups have dealt with clinical heterogeneity and to seek out best practices for addressing clinical heterogeneity in systematic reviews (SRs) and comparative effectiveness reviews (CERs). Such best practices, to the extent they exist, may enable AHRQ's EPCs to address critiques from patients, clinicians, policymakers, and other proponents of health care about the extent to which “average” estimates of the benefits and harms of health care interventions apply to individual patients or to small groups of patients sharing similar characteristics. Such users of reviews often assert that EPC reviews typically focus on broad populations and, as a result, often lack information relevant to patient subgroups that are of particular concern to them. More important, even when EPCs evaluate literature on homogeneous groups, there may be varying individual treatment for no apparent reason, indicating that average treatment effect does not point to the best treatment for any given individual. Thus, the health care community is looking for better ways to develop information that may foster better medical care at a “personal” or “individual” level. To address our charge for this methods project, the EPC set out to answer six key questions (KQ). Key questions for methods report on clinical heterogeneity include: 1. What is clinical heterogeneity? a. How has it been defined by various groups? b. How is it distinct from statistical heterogeneity? c. How does it fit with other issues that have been addressed by the AHRQ Methods Manual for CERs? 2. How have systematic reviews dealt with clinical heterogeneity in the key questions? a. What questions have been asked? b. How have they pre-identified population subgroups with common clinical characteristics that modify their intervention-outcome association? c. What are best practices in key questions and how these subgroups have been identified? 3. How have systematic reviews dealt with clinical heterogeneity in the review process? a. What do guidance documents of various systematic review groups recommend? b. How have EPCs handled clinical heterogeneity in their reviews? c. What are best practices in searching for and interpreting results for particular subgroups with common clinical characteristics that may modify their intervention-outcome association? 4. What are critiques in how systematic reviews handle clinical heterogeneity? a. What are critiques from specific reviews (peer and public) on how EPCs handled clinical heterogeneity? b. What general critiques (in the literature) have been made against how systematic reviews handle clinical heterogeneity? 5. What evidence is there to support how to best address clinical heterogeneity in a systematic review? 6. What questions should an EPC work group on clinical heterogeneity address? Heterogeneity (of any type) in EPC reviews is important because its appearance suggests that included studies differed on one or more dimensions such as patient demographics, study designs, coexisting conditions, or other factors. EPCs then need to clarify for clinical and other audiences, collectively referred to as stakeholders, what are the potential causes of the heterogeneity in their results. This will allow the stakeholders to understand whether and to what degree they can apply this information to their own patients or constituents. Of greatest importance for this project was clinical heterogeneity, which we define as the variation in study population characteristics, coexisting conditions, cointerventions, and outcomes evaluated across studies included in an SR or CER that may influence or modify the magnitude of the intervention measure of effect (e.g., odds ratio, risk ratio, risk difference).
  published research article that uses chi square test: Statistics for Terrified Biologists Helmut F. van Emden, 2019-07-09 Makes mathematical and statistical analysis understandable to even the least math-minded biology student This unique textbook aims to demystify statistical formulae for the average biology student. Written in a lively and engaging style, Statistics for Terrified Biologists, 2nd Edition draws on the author’s 30 years of lecturing experience to teach statistical methods to even the most guarded of biology students. It presents basic methods using straightforward, jargon-free language. Students are taught to use simple formulae and how to interpret what is being measured with each test and statistic, while at the same time learning to recognize overall patterns and guiding principles. Complemented by simple examples and useful case studies, this is an ideal statistics resource tool for undergraduate biology and environmental science students who lack confidence in their mathematical abilities. Statistics for Terrified Biologists presents readers with the basic foundations of parametric statistics, the t-test, analysis of variance, linear regression and chi-square, and guides them to important extensions of these techniques. It introduces them to non-parametric tests, and includes a checklist of non-parametric methods linked to their parametric counterparts. The book also provides many end-of-chapter summaries and additional exercises to help readers understand and practice what they’ve learned. Presented in a clear and easy-to-understand style Makes statistics tangible and enjoyable for even the most hesitant student Features multiple formulas to facilitate comprehension Written by of the foremost entomologists of his generation This second edition of Statistics for Terrified Biologists is an invaluable guide that will be of great benefit to pre-health and biology undergraduate students.
  published research article that uses chi square test: Quantitative Research in Communication Mike Allen, Scott Titsworth, Stephen K. Hunt, 2008-09-12 Written for communication students, Quantitative Research in Communication provides practical, user-friendly coverage of how to use statistics, how to interpret SPSS printouts, how to write results, and how to assess whether the assumptions of various procedures have been met. Providing a strong conceptual orientation to techniques and procedures that range from the moderately basic to highly advanced, the book provides practical tips and suggestions for quantitative communication scholars of all experience levels. In addition to important foundational information, each chapter that covers a specific statistical procedure includes suggestions for interpreting, explaining, and presenting results; realistic examples of how the procedure can be used to answer substantive questions in communication; sample SPSS printouts; and a detailed summary of a published communication journal article using that procedure. Features · Engaged Research application boxes stimulate thought and discussion, illustrating how particular research methods can be used to answer very practical, civic-minded questions. · Realistic examples at the beginning of each chapter show how the chapter′s procedure could be used to answer a substantive research question. · Examples and application activities geared toward the emerging trend of service learning encourage students to do projects oriented toward their community or campus. · Summaries of journal articles demonstrate how to write statistical results in APA style and illustrate how real researchers use statistical procedures in a wide variety of contexts, such as tsunami warnings, date requests, and anti-drug public service announcements. · How to Decipher Figures show students how to read the statistical shorthand presented in the quantitative results of an article and also, by implication, show them how to write up results . Quantitative Research in Communication is ideal for courses in Quantitative Methods in Communication, Statistical Methods in Communication, Advanced Research Methods (undergraduate), and Introduction to Research Methods (Graduate) in departments of communication, educational psychology, psychology, and mass communication.
  published research article that uses chi square test: Statistics from A to Z Andrew A. Jawlik, 2016-09-21 Statistics is confusing, even for smart, technically competent people. And many students and professionals find that existing books and web resources don’t give them an intuitive understanding of confusing statistical concepts. That is why this book is needed. Some of the unique qualities of this book are: • Easy to Understand: Uses unique “graphics that teach” such as concept flow diagrams, compare-and-contrast tables, and even cartoons to enhance “rememberability.” • Easy to Use: Alphabetically arranged, like a mini-encyclopedia, for easy lookup on the job, while studying, or during an open-book exam. • Wider Scope: Covers Statistics I and Statistics II and Six Sigma Black Belt, adding such topics as control charts and statistical process control, process capability analysis, and design of experiments. As a result, this book will be useful for business professionals and industrial engineers in addition to students and professionals in the social and physical sciences. In addition, each of the 60+ concepts is covered in one or more articles. The 75 articles in the book are usually 5–7 pages long, ensuring that things are presented in “bite-sized chunks.” The first page of each article typically lists five “Keys to Understanding” which tell the reader everything they need to know on one page. This book also contains an article on “Which Statistical Tool to Use to Solve Some Common Problems”, additional “Which to Use When” articles on Control Charts, Distributions, and Charts/Graphs/Plots, as well as articles explaining how different concepts work together (e.g., how Alpha, p, Critical Value, and Test Statistic interrelate). ANDREW A. JAWLIK received his B.S. in Mathematics and his M.S. in Mathematics and Computer Science from the University of Michigan. He held jobs with IBM in marketing, sales, finance, and information technology, as well as a position as Process Executive. In these jobs, he learned how to communicate difficult technical concepts in easy - to - understand terms. He completed Lean Six Sigma Black Belt coursework at the IASSC - accredited Pyzdek Institute. In order to understand the confusing statistics involved, he wrote explanations in his own words and graphics. Using this material, he passed the certification exam with a perfect score. Those statistical explanations then became the starting point for this book.
  published research article that uses chi square test: Statistical Methods for Categorical Data Analysis Daniel Powers, Yu Xie, 2008-11-13 This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/
  published research article that uses chi square test: Between Facts and Norms Pascal Borry, 2005
  published research article that uses chi square test: The Analysis of Categorical Data R. L. Plackett, 1974 The poisson distribution; Single classifications; Two-way classifications; 2 x 2 tables; r X s tables; Models and methods; Three-way classifications; Matching; Multivariate data.
  published research article that uses chi square test: Small Clinical Trials Institute of Medicine, Board on Health Sciences Policy, Committee on Strategies for Small-Number-Participant Clinical Research Trials, 2001-01-01 Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a large trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.
  published research article that uses chi square test: Cartoon Guide to Statistics Larry Gonick, 1993-07-14 If you have ever looked for P-values by shopping at P mart, tried to watch the Bernoulli Trails on People's Court, or think that the standard deviation is a criminal offense in six states, then you need The Cartoon Guide to Statistics to put you on the road to statistical literacy. The Cartoon Guide to Statistics covers all the central ideas of modern statistics: the summary and display of data, probability in gambling and medicine, random variables, Bernoulli Trails, the Central Limit Theorem, hypothesis testing, confidence interval estimation, and much more—all explained in simple, clear, and yes, funny illustrations. Never again will you order the Poisson Distribution in a French restaurant!
  published research article that uses chi square test: Shopping Tourism, Retailing and Leisure Dallen J. Timothy, 2005-03-14 Shopping Tourism, Retailing and Leisure provides a comprehensive examination of the relationships between tourism, leisure, shopping, and retailing. Critical issues are examined within the framework of the dichotomous relationship between utilitarian and hedonic forms of shopping, shopping as a primary and secondary attraction in tourist destinations, the development of various tourist-retail venues, the role of souvenirs in tourism, and management issues (e.g. merchandising, venue design, and customer service).
  published research article that uses chi square test: Experimental and Quasi-Experimental Designs for Research Donald T. Campbell, Julian C. Stanley, 2015-09-03 We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.
  published research article that uses chi square test: Cochrane Handbook for Systematic Reviews of Interventions Julian P. T. Higgins, Sally Green, 2008-11-24 Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves.
  published research article that uses chi square test: Distillation Engineering Research and Development in the USSR. United States Department of Commerce. Office of Technical Services, 1960
  published research article that uses chi square test: The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation Bruce B. Frey, 2018-01-29 In an era of curricular changes and experiments and high-stakes testing, educational measurement and evaluation is more important than ever. In addition to expected entries covering the basics of traditional theories and methods, other entries discuss important sociopolitical issues and trends influencing the future of that research and practice. Textbooks, handbooks, monographs and other publications focus on various aspects of educational research, measurement and evaluation, but to date, there exists no major reference guide for students new to the field. This comprehensive work fills that gap, covering traditional areas while pointing the way to future developments. Features: Nearly 700 signed entries are contained in an authoritative work spanning four volumes and available in choice of electronic and/or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of education research, measurement, and evaluation to more easily locate directly related entries. (For instance, sample themes include Data, Evaluation, Measurement Concepts & Issues, Research, Sociopolitical Issues, Standards.) Back matter includes a Chronology of the development of the field; a Resource Guide to classic books, journals, and associations; and a detailed Index. Entries conclude with References/Further Readings and Cross References to related entries. The Index, Reader’s Guide themes, and Cross References will combine to provide robust search-and-browse in the e-version.
  published research article that uses chi square test: Methods in Psychological Research Bryan J. Rooney, Annabel Ness Evans, 2018-08-01 Methods in Psychological Research introduces students to the rich world of research in psychology through student-friendly writing, compelling real-world examples, and frequent opportunities for practice. Using a relaxed yet supportive tone that eases student anxiety, the authors present a mixture of conceptual and practical discussions, and spark reader interest in research by covering meaningful topics that resonate with today’s students. In-text features like Conceptual Exercises, FYI sections, and FAQ sections with accompanying visual cues support learning throughout the research experience. The Fourth Edition equips students with the tools they need to understand research concepts, conduct their own experiments, and present their findings.
  published research article that uses chi square test: Joint Statistical Papers Jerzy Neyman, E. S. Pearson, 2023-11-15
  published research article that uses chi square test: Social Science Research Anol Bhattacherjee, 2012-04-01 This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
  published research article that uses chi square test: Encyclopedia of Public Health Wilhelm Kirch, 2008-06-13 The Encyclopedic Reference of Public Health presents the most important definitions, principles and general perspectives of public health, written by experts of the different fields. The work includes more than 2,500 alphabetical entries. Entries comprise review-style articles, detailed essays and short definitions. Numerous figures and tables enhance understanding of this little-understood topic. Solidly structured and inclusive, this two-volume reference is an invaluable tool for clinical scientists and practitioners in academia, health care and industry, as well as students, teachers and interested laypersons.
  published research article that uses chi square test: An Introduction to Statistics Kieth A. Carlson, Jennifer R. Winquist, 2021-01-10 This updated and reorganized Third Edition of this textbook takes a workbook-style approach that encourages an active approach to learning statistics. Carefully placed reading questions throughout each chapter allow students to apply their knowledge right away, while in-depth activities based on current behavioral science scenarios, each with problem sets and quiz questions, give students the opportunity to assess their understanding of concepts while reading detailed explanations of more complex statistical concepts. Additional practice problems further solidify student learning. Most activities are self-correcting, so if a concept is misunderstood, this misunderstanding is corrected early in the learning process. After working through each chapter, students are far more likely to understand the material than when they only read the material.
  published research article that uses chi square test: Sex Bias in Autoimmunity: From Animal Models to Clinical Research and Applications Coziana Ciurtin, Veena Taneja, Elizabeth C Jury, 2023-01-17 Autoimmune diseases are characterized by an abnormal and self-directed immune response leading to damage and dysfunction of multiple organs and tissues. Most autoimmune diseases are recognized as affecting disproportionately more women than men, suggesting a crucial role of sex hormones in modulating immune responses, with estrogens being postulated as enhancing autoimmunity and androgens playing a protective role. It is also widely acknowledged that there is an overwhelming male bias in non-human (animal) studies of autoimmune diseases, while studies of both sexes in human research frequently fail to analyze results by sex. Underrepresentation of females in animal models of autoimmune disease is often justified by their intrinsic variability during the reproductive period, compromising the understanding of impact of the female sex chromosome and hormones on immune system functions leading to the high prevalence of autoimmune conditions. This Research Topic will highlight the most recent advances in understanding the possible mechanisms for sex-specific differences in autoimmunity, with a specific focus on pre-clinical animal and human models of autoimmune inflammation, as well as on the most common sex specific differences in autoimmune diseases. The topic will emphasize advances in research exploring sex determinants in autoimmune rheumatic diseases such as systemic lupus erythematosus, rheumatoid arthritis, spondyloarthritis, psoriatic arthritis, Sjӧgren's syndrome and further diseases such as inflammatory bowel disease, autoimmune hepatitis, multiple sclerosis, psoriasis, asthma and more. The present Research Topic will include both full length and short research communications, as well as perspective and review articles addressing various aspects of sex biased differences in pathogenesis, age at disease onset, clinical manifestations, disease course, treatment response, associated co-morbidities and overall survival across different autoimmune diseases.
  published research article that uses chi square test: Proceedings of the International Conference on Sports Science and Health (ICSSH 2022) Yulingga Nanda Hanief, Rama Kurniawan, Tika Dwi Tama, Dian Mawarni, Anindya Hapsari, Nurhasmadiar Nandini, Erni Astutik, Mika Vernicia Humairo, 2023-02-10 This is an open access book. The year 2022 is the year when people begin to rise from the impact of the Covid 19 pandemic that occurred for approximately 2 years before this. During the pandemic there was a lot of weakening of activities in various sectors. The weakening led to the community's economy. The sports sector is also feeling the impact. Where all sports activities encounter obstacles such as sports competition activities, sports training, sports education and sports health services to the community. These obstacles have an impact on the economic decline of sports players. However, in 2022, all sporting activities are slowly restarting but still with due observance of health and safety protocols. Therefore, it is necessary to have discussions and access references to provide knowledge in starting activities in the sports sector after the Covid-19 Pandemic. Because indeed sports actors need to get mental support, knowledge and direction to start reviving sports activities in order to accelerate economic recovery. The Faculty of Sports Science, State University of Malang welcomes you to join the 6th International Conference on Sports Sciences and Health (6th ICCSH 2022). This conference focuses on how aspects of sport and health deal with issues in management, technology and innovation of sports and education as well as in scientific issues. Collaboration and knowledge sharing will be a great opportunity to overcome potential challenges that grow dynamically following the development of sports after the Covid-19 Pandemic.