1
github-repo: rstudio/bookdown-demo
License
2
Intro to R
2.1
Getting started with R
2.2
The R Programming Language
2.3
Getting Started
2.4
Getting used to RStudio
2.5
Running code
2.6
Commenting
2.7
Arithmetic operations
2.7.1
Order of operations
2.8
Your turn
2.9
Objects
2.9.1
Naming an object
2.10
Data structure
2.10.1
Scalars
2.10.2
Vectors
2.10.3
Subsetting
2.11
Your turn
2.12
A peak into next time:
3
Data Structure (cont.) & RMarkdown
Data Structure
3.1
Matrix
3.2
Data frame
3.3
Your turn
R Markdown
3.4
Basics of R Markdown
3.4.1
Creating a new R Markdown file
3.4.2
Knitting a document
3.4.3
Writing code chunks
3.4.4
Structure of a document
4
Control Flow & Functions
4.1
Logicals
4.2
if
statement
4.3
Your turn
4.4
for
loops
4.5
for
loop with an
if
statement
4.6
Your turn
4.7
A Basic Example
4.8
Functions with control flows
4.9
Logical/String as inputs
4.10
Multiple outputs as a list
5
CTT Item Analysis
5.1
Response data
5.2
CTT Item Analysis
5.2.1
Total score
5.2.2
Item difficulty
5.2.3
Item discrimination
5.3
Coefficient
\(\alpha\)
5.4
KR20
5.5
KR21
5.6
Standard error of measurement
5.6.1
Confidence interval for true score
5.7
Your turn
6
Validity
6.1
read.table
6.2
Criterion Related Validity
6.2.1
Correction for attenuation
6.3
Binomial distribution
6.4
Normal distribution
6.5
Uniform distribution
6.6
Your turn
7
Linear Regression
7.1
cats
dataset from
MASS
package
7.2
Simple Linear Regression
7.3
lm()
function
8
Decision Table
8.1
Decision Table
8.2
Hit Rate
8.3
Sensitivity and Specificity
8.4
Base Rate
8.5
Exploratory Factor Analysis
8.5.1
factanal()
function
8.5.2
EFA with Covariance Matrix
8.5.3
Factor scores
8.5.4
Rotational Indeterminacy
8.5.5
fa()
function in
psych
package
8.6
Your turn
9
Test Construction
9.1
Item Analysis: Item Reliability and Validity Indices
9.1.1
Item Difficulty
9.1.2
Item Discrimination
9.1.3
Item-score SD
9.1.4
Item Reliability
9.1.5
Item Validity
9.2
Test Construction Using Item Indices
9.2.1
Maximizing Internal Consistency Reliability
9.2.2
Maximizing Validity Coefficient
9.2.3
Balancing Two Conflicting Objectives
10
Transforming
10.1
Percentiles
10.1.1
Frequency Distribution
10.1.2
Calculating Percentile
10.1.3
Trait Value Corresponding to Given Percentile
10.2
Standard and Standardized Scores
10.3
Normalized Scores
10.3.1
T-scores
10.3.2
Stanines
10.4
Thurstone’s Absolute Scaling Method
11
Item Response Theory 1
11.1
Item Characteristic Curves (ICC)
11.1.1
Item parameters
11.1.2
Drawing ICC plots
11.2
Simulating Data Under IRT Models
12
Item Response Theory 2
12.1
IRT ability (
\(\theta\)
) estimation
12.2
IRT item parameter estimation
12.2.1
Part 1: Estimate item parameters by MMLE.
12.2.2
Part 2: Estimate latent
\(\theta\)
s by CMLE.
12.3
Information Function
12.3.1
Item Information Function
12.3.2
Test Information Function and Standard Error
13
DIF Detection
13.1
Mantel-Haenszel
13.2
Multiple-group IRT
13.3
Comparing ICCs
14
IER
14.1
Long String
14.1.1
MaxLongString
14.1.2
AveLongStrong
14.2
Psychometric Synonym/Antonym
14.2.1
Step 1
14.2.2
Step 2
14.3
Even-Odd Consistency
14.4
Mahalanobis Distance
14.4.1
Flagged examinees
R Programming for Psychometrics
Week 3
Data Structure (cont.) & RMarkdown