Group Iterative Multiple Model Estimation (GIMME)

KM Gates

2019-05-23

The Basics

Running GIMME

1. Create two new folders (i.e., directories)

2. Extract the time series for your variables

3. Installing gimme with R

4. Running gimme The gimme (or equivelantly, gimmeSEM) function requires that you input: 1. Source directory 2. How data are separated (e..g, comma-separated values) 3. If there is a header

All other fields are optional and will go to defaults if no user input is provided. If no output directory is indicated, all information is stored as R objects (see tutorial linked above for details).

gimme(                  # can use "gimme" or "gimmeSEM"
    data = '',          # source directory where your data are 
    out = '',           # output directory where you'd like your output to go
    sep = "",           # how data are separated. "" for space; "," for comma, "/t" for tab-delimited
    header = ,          # TRUE or FALSE, is there a header
    ar = TRUE,          # TRUE (default) or FALSE, start with autoregressive paths open
    plot = TRUE,        # TRUE (default) or FALSE, generate plots
    subgroup = FALSE,   # TRUE or FALSE (default), cluster individuals based on similarities in effects
    paths = NULL,       # option to list paths that will be group-level (semi-confirmatory)
    groupcutoff = .75,  # the proportion that is considered the majority at the group level
    subcutoff = .5      # the proportion that is considered the majority at the subgroup level
    )        

While gimme is running you will see information iterate in the command window. The algorithm will tell you when it is finished.

Output

FAQ

How many time points do I need? This is a difficult question since it will be related to the number of variables you are using. Rules of thumb for any analysis can generally be used: the more the better! Having at lest 100 time points is recommended, but adequate results have been obtained in simulation studies with only T = 60.

Do all individuals have to have the same number of observations (T)? No.

How many people do I need in my sample? For regular gimmme, reliable results are obtained with as few as 10 participants. Remember that in this context, power to detect effects is determined by the number of time points rather than the number of individuals. Still, having at least 10 individuals helps gimme to detect signal from noise by looking for effects that consistently occur.

What do I do if I obtain an error? Do some initial trouble-shooting. 1. Ensure that all of your individuals have the same number of variables (columns) in their data sets. 2. Ensure that all variables have variability (i.e., are not constant). gimme will let you know if this is the case. 3. Ensure your path directories are correct. 4. Ensure that the columns are variables and the rows contain the observations across time. 5. If all this is correct, please email the error you received, code used to run gimme, and the data (we promise not to use it or share it) to: echo gimme@unc.edu.