Longitudinal Data Analysis

Post-workshop material on Dual Change Score Model

Dual Change Score Model - HTML Slide show (html)

Some other goodies

What "Quality of numerical results" means (via Mplus Discussion)
Materials in development
- Slides on multilevel curve of factors model (html)
- Slides on multilevel curve of factors model with categorical data (html)

# Load SAVEDATA from OUT file

devtools::source_url("https://raw.githubusercontent.com/rnj0nes/RNJmisc/master/runmplus_load_savedata.R")

setwd("~/Downloads/")

res <- runmplus_load_savedata("ex0204.out")

df <- res$data

skimr::skim(df)

── Data Summary ────────────────────────

Values

Name df

Number of rows 14059

Number of columns 11

_______________________

Column type frequency:

numeric 11

________________________

Group variables None

── Variable type: numeric ────────────────────────────────────────────────────────────────────────────────────────────────

skim_variable n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist

1 msqtot1 361 0.974 4.77 1.27 0 4 5 6 6 ▁▁▁▂▇

2 msqtot4 3160 0.775 4.73 1.35 0 4 5 6 6 ▁▁▁▂▇

3 msqtot7 5890 0.581 4.57 1.43 0 4 5 6 6 ▁▁▁▂▇

4 male 0 1 -0.000448 0.485 -0.378 -0.378 -0.378 0.622 0.622 ▇▁▁▁▅

5 black 0 1 0.000458 0.397 -0.196 -0.196 -0.196 -0.196 0.804 ▇▁▁▁▂

6 i 0 1 4.77 0.792 1.40 4.41 4.98 5.36 5.75 ▁▁▂▅▇

7 i_se 0 1 0.512 0.0623 0.468 0.468 0.468 0.508 0.656 ▇▃▁▁▃

8 s 0 1 -0.0305 0.273 -1.36 -0.185 -0.024 0.145 0.789 ▁▁▅▇▁

9 s_se 0 1 0.476 0.0406 0.442 0.442 0.442 0.505 0.539 ▇▁▁▃▃

10 q 0 1 -0.241 0.112 -0.479 -0.206 -0.206 -0.156 -0.156 ▂▁▁▁▇

11 q_se 0 1 0 0 0 0 0 0 0 ▁▁▇▁▁