2022년 11월 12일 토요일

easier R than SPSS with Rcmdr : Contents

 

easier R than SPSS
with Rcmdr
 

Written by Jeehyoung Kim


 

foreword

 

This book covers statistical tests for beginners.

Some time ago I was talking with a professor of statistics, who told me that she wanted to have a program that was suitable for teaching students. SPSS is an easy GUI method to teach to the general public, but it’s expensive. Because R is script-based, it is difficult to teach to the general public.

Rcmdr provides easier menu configuration and more intuitive results and graphs than SPSS. It is also highly expandable and will be a bridge that leads to a wider world of R.

 The first target readers I considered in writing this book is the students. The second readers are the professors who teach the students. Most of professors will be familiar with R, SAS, or SPSS. But what professors are familiar with and what professors tell their students about it is another completely different part of the challenge. I have that difficulty, too. If you’re looking for a program with easy-to-teach menus, a program that’s never lacking in functionality, first take a quick look at this book. Then you’ll find that this is a tool that’s easier to learn and use than SPSS.

 

Aug 2022

Jeehyoung Kim

 

Contents

Part 1 Basic Statistics

ch.1 Installation. 7

ch.2 t-test 13

ch.3 Nomality test and Variances test 26

ch.4 Wilcoxon rank sum test 34

ch.5 Better Plots 39

ch.6 ANOVA.. 53

ch.7 2-way ANOVA.. 59

ch.8 ANCOVA.. 66

ch.9 Kruskal-Wallis test 70

ch.10 Chi-squared test 73

ch.11 Correlations 86

ch.12 Linear regression. 99

ch.13 Logistic regression. 112

Part 2 (ch. 14-16) Survival Analysis

ch.14 KM curve and log-rank test 125

ch.15 Logrank trend test 132

ch.16 Cox regression. 134

Part 3 (ch. 17-19) Statistics on Diagnosis

ch.17 ROC.. 148

ch.18 Sensitivity and Specificity. 162

ch.19 Kappa statistics for agreement 164

Part 4 (ch. 20-22) Analysis of paired data

ch.20 Paired t-test and Wilcoxon signed rank test 169

ch.21 Repeated-Measures ANOVA and Friedman test 177

ch.22 McNemar test Cochran Q test 196

ch.23 Propensity Score Matching and Analysis 201

Part 5 (ch. 24-27) Dimensional Analysis

ch.24 Principal Component Analysis (PCA) 222

ch.25 Factor Analysis 230

ch.26 Cluster analysis 236

ch.27 Factor analysis and cluster analysis 253

Part 6 (ch. 28-34) Samples Size Calculation

ch.28 proportion of two groups 256

ch.29 mean of two groups 260

ch.30 paired mean of two groups 263

ch.31 two survival curves 265

ch.32 Calculation of power 269

ch.33 Many other studies 272

ch.34 Meaning of sample size (power) calculation. 275

Part 7 (ch. 35-41) Uploading and Editing Data

ch.35 Uploading your data. 288

ch.36 Removing missing values 297

ch.37 Calculating and inserting new variables 298

ch.38 Variable standardization. 300

ch.39 Continuous variable as interval variable. 302

ch.40 number as a nominal variable. 309

ch.41 Reorder factor levels 312

ch.42 Original menu and New menu. 314

Closing. 318

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  • R data visualization book 2
https://tinyurl.com/R-plot-II-2  simple variables
https://tinyurl.com/R-plot-II-3-4   many variables / map
https://tinyurl.com/R-plot-II-5-6   time related / statistics related
https://tinyurl.com/R-plot-II-7-8   others / reactive chart 
 



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