R for Psych Handbook
1
Preface
2
Introduction to R
2.1
Getting Started
2.2
A Note on Setting the Working Directory
2.3
The Basics
2.4
R as Calculator
2.5
Data Exploration
2.6
Indexing
2.7
Whirlwind Tour of R
2.8
Functions for Psychologists
2.9
Resources
2.9.1
Template Stuff
3
Data Manipulation in R
3.1
Cleaning Response Data
3.1.1
Cleaning Up Gender
3.2
Merging Data
3.3
Checking for Univariate Outliers
3.3.1
Checking for Multivariate Outliers
3.3.2
Checking for Skew and Kurtosis
3.3.3
Exporting Data
4
Epistemology of Statistics
4.1
Karl Popper
4.2
R.A. Fisher
4.3
Neyman-Pearson
4.4
Bayes
5
Descriptive Statistics, z Scores, Central Limit
5.1
Descriptive Statistics and the Normal Distribution
5.1.1
Organizing Data
5.1.2
Shape of Data
5.1.3
Important Considerations for Central Tendency
5.1.4
Measures of Variability
5.1.5
Properties of z Scores
5.2
Practice
6
Sampling Distributions
7
Hypothesis Testing
7.1
Steps of Hypothesis Testing
7.1.1
Other important considerations.
7.2
Two Sample
8
Power, Confidence Intervals, Effect Size Measures
8.1
Power
8.1.1
Test Equations
8.1.2
Factors of Power
8.2
Confidence Ientervals
8.2.1
Capture Percentage
9
Correlation
9.1
Calculating Person’s r
9.1.1
Assumptions
9.2
Testing the significance of the correlation coefficient.
9.3
Spearman’s Rho
10
Regression
11
Matched T Test
11.1
Theory
12
One Way ANOVA
12.1
Theory
12.1.1
Type I Error Rates
12.1.2
The F Test
12.1.3
The Grand Mean
12.1.4
ANOVA Assumptions
12.2
Practice
12.2.1
Step Three
12.2.2
Running The Calulation in R
12.2.3
Assumptions of ANOVA
12.2.4
Practice
12.3
Effect Size Measures
13
Multiple Comparisons
13.1
Trend analysis
14
Factorial Anova
14.1
Assumptions of ANOVA
14.2
Power and Sample Size Estimatoin
14.2.1
Three Way Factorial
15
Repeated Measures ANOVA:
15.1
Assumptions of RMANOVA
15.2
Effect Size
15.3
DB Notes
15.3.1
AF Example
16
Factorial Designs with Repeated Measures
16.1
Assumptions of Mixed ANOVA
16.1.1
Equal Variance
16.1.2
Simple Main Effects
17
Multiple Regression
17.1
Conceptual Representation
17.1.1
Second Part
18
Chi-Square
19
Non-Parametric Data
20
Advanced Data Cleaning
21
Advanced Multiple Regression
21.1
OLD MEDIATION MODERATION
22
Logistic Regression
23
Mediation and Moderation
24
ANCOVA
24.1
Theory
24.1.1
Reducing Noise
24.1.2
Assumptions of ANOVA
24.1.3
Best Practice
24.2
Practice
25
MANOVA
26
Repeated Measures ANOVA
26.0.1
Null Hypothesis
26.0.2
Strength of association
26.0.3
Limitation
26.0.4
Doubly Repeated MANOVA
26.0.5
Post Tests
26.0.6
Testing interactions - Simple Effects, Simple Comparisons and Interaction Contrasts
26.1
Practice
27
Factor Analysis
27.1
Theory
27.1.1
Factor Analysis Purposes
27.1.2
Types of Analysis
27.1.3
PCA
27.1.4
Rotatation
27.1.5
Assumptions
27.1.6
Problems wiht Catheorica Variables
27.1.7
Running It
27.2
Practice
27.2.1
Data Preparation
27.2.2
Analysis I
27.2.3
Analysis I
28
Mixed Effects Models
29
Latent Variable Modeling – Path, SEM, CFA
29.1
Path Analysis
29.1.1
Background
29.1.2
Getting Numeric
29.1.3
Doing It in R
29.1.4
An Example In R
29.1.5
Indirect Effects
29.2
Basic Latent Variable Models , SEM
29.2.1
Background
29.2.2
Latent Variable Models
29.2.3
Doing it With Two Latent Variables in R
29.2.4
Doing SEM in R
29.2.5
Reporting Results
30
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References
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R for Psych Handbook
Chapter 30
This is a template file
Template file