Determining sample size and power in research studies a manual for researchers /
Verma, J. P.
Determining sample size and power in research studies a manual for researchers / J.P. Verma, Priyam Verma. - Singapore : Springer, 2020. - viii,127 p. : ill. ; 24 cm.
Description based upon print version of record.
Includes bibliographical references.
Intro -- Foreword -- Preface -- Acknowledgements -- Contents -- About the Authors -- 1 Introduction to Sample Size Determination -- Introduction -- Issues with Very Small Samples -- Issues with Very Large Samples -- Strategy in Sample Selection -- Common Errors in Conducting Research -- Flow Diagrams for Deciding Sample Size -- Summary -- Bibliography -- 2 Understanding Statistical Inference -- Introduction -- Hypothesis Testing -- Procedure in Hypothesis Testing Experiment -- Effect Size -- Summary -- Bibliography -- 3 Understanding Concepts in Estimating Sample Size in Survey Studies Introduction -- Determining Sample Size in Estimating Population Mean -- Factors Affecting Sample Size -- Sample Size Determination for Estimating Mean When Population SD Is Known -- Sample Size Determination for Estimating Mean When Population SD Is Unknown -- Determining Sample Size in Estimating Population Proportion -- Sample Size Determination for Estimating Proportion -- Determining Sample Size in Estimating Difference Between Two Population Means -- Summary -- Bibliography -- 4 Understanding Concepts in Estimating Sample Size in Hypothesis Testing Experiments -- Introduction Importance of Sample Size in Experimental Studies -- Sample Size on the Basis of Power -- One-Sample Testing of Mean -- Determining Sample Size -- Estimation of Sample Size in One-Sample Test -- Estimation of Minimum Detectable Difference -- Estimation of Power in One-Sample t-Test -- Testing Difference Between Two Means -- Determining Sample Size in Two-Sample t-Test -- Estimation of Power in Two-Sample t-Test -- Summary -- Bibliography -- 5 Use of G*Power Software -- Introduction -- Procedure of Installing G*Power 3.1 -- Summary -- Bibliography 6 Determining Sample Size in Experimental Studies -- Introduction -- One Sample Tests -- Two Sample Tests -- Testing Significance of Relationship -- Summary -- Bibliography -- 7 Determining Sample Size in General Linear Models -- Introduction -- Linear Multiple Regression Model -- Logistic Regression -- Analysis of Variance -- Summary -- Bibliography -- Appendix
This book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.
9789811552038
com.springer.onix.9789811552045 Springer Nature
Sampling (Statistics)
Experimental design.
Social research & statistics.
Probability & statistics.
Study & learning skills: general.
Social Science--Sociology--General.
Mathematics--Probability & Statistics--General.
Experimental design
Sampling (Statistics)
519.52 / VED
Determining sample size and power in research studies a manual for researchers / J.P. Verma, Priyam Verma. - Singapore : Springer, 2020. - viii,127 p. : ill. ; 24 cm.
Description based upon print version of record.
Includes bibliographical references.
Intro -- Foreword -- Preface -- Acknowledgements -- Contents -- About the Authors -- 1 Introduction to Sample Size Determination -- Introduction -- Issues with Very Small Samples -- Issues with Very Large Samples -- Strategy in Sample Selection -- Common Errors in Conducting Research -- Flow Diagrams for Deciding Sample Size -- Summary -- Bibliography -- 2 Understanding Statistical Inference -- Introduction -- Hypothesis Testing -- Procedure in Hypothesis Testing Experiment -- Effect Size -- Summary -- Bibliography -- 3 Understanding Concepts in Estimating Sample Size in Survey Studies Introduction -- Determining Sample Size in Estimating Population Mean -- Factors Affecting Sample Size -- Sample Size Determination for Estimating Mean When Population SD Is Known -- Sample Size Determination for Estimating Mean When Population SD Is Unknown -- Determining Sample Size in Estimating Population Proportion -- Sample Size Determination for Estimating Proportion -- Determining Sample Size in Estimating Difference Between Two Population Means -- Summary -- Bibliography -- 4 Understanding Concepts in Estimating Sample Size in Hypothesis Testing Experiments -- Introduction Importance of Sample Size in Experimental Studies -- Sample Size on the Basis of Power -- One-Sample Testing of Mean -- Determining Sample Size -- Estimation of Sample Size in One-Sample Test -- Estimation of Minimum Detectable Difference -- Estimation of Power in One-Sample t-Test -- Testing Difference Between Two Means -- Determining Sample Size in Two-Sample t-Test -- Estimation of Power in Two-Sample t-Test -- Summary -- Bibliography -- 5 Use of G*Power Software -- Introduction -- Procedure of Installing G*Power 3.1 -- Summary -- Bibliography 6 Determining Sample Size in Experimental Studies -- Introduction -- One Sample Tests -- Two Sample Tests -- Testing Significance of Relationship -- Summary -- Bibliography -- 7 Determining Sample Size in General Linear Models -- Introduction -- Linear Multiple Regression Model -- Logistic Regression -- Analysis of Variance -- Summary -- Bibliography -- Appendix
This book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.
9789811552038
com.springer.onix.9789811552045 Springer Nature
Sampling (Statistics)
Experimental design.
Social research & statistics.
Probability & statistics.
Study & learning skills: general.
Social Science--Sociology--General.
Mathematics--Probability & Statistics--General.
Experimental design
Sampling (Statistics)
519.52 / VED