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gimme (version 0.7-15)

Group Iterative Multiple Model Estimation

Description

Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) .

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Install

install.packages('gimme')

Monthly Downloads

827

Version

0.7-15

License

GPL-2

Issues

0

Pull Requests

0

Stars

28

Forks

18

Maintainer

KM Gates

Last Published

August 29th, 2023

Functions in gimme (0.7-15)

recode.vars

Recode variable names.
predict.gimme

GIMME Predicted Values.
subgroupStage

Create structure of group search solutions.
ms.fit

Fitted gimme object with multiple solutions
simulateVAR

Simulate data from Vector AutoRegression (VAR) models.
setupFinalDataChecks

Do some final checks on the data.
setupDataLists

Create a list of dataframes
summaryPathsCounts

Create summary matrix of path counts and subgroup plots
solution.tree

Solution trees for multiple solutions gimme.
indSEM

Individual-level structural equation model search.
indiv.search

Individual-level search. Used in gimmeSEM, aggSEM, indSEM.
highest.mi

Identifies highest MI from list of MIs.
search.paths

Searches for paths. Ties together highest.mi and return.mis functions.
sFIR

Estimate response function for each person using smoothed Finite Impulse Response.
indiv.search.ms

Individual-level search. Used in gimmeSEM, aggSEM, indSEM.
residuals.gimme

GIMME Residuals.
search.paths.ms

Searches for paths. Ties together highest.mi and return.mis functions.
prune.paths

Prunes paths. Ties together lowest.z and return.zs functions.
gimmems.write

Write MS-GIMME results to data.frame.
return.mis

Returns MIs from lavaan fit object.
gimmeSEM

Group iterative multiple model estimation.
setupMultVarNames

Get names for bilinear effects.
setupPrelimDataChecks

Do some preliminary checks on the data.
simDataLV

Latent variable example, heterogeneous data, group, subgroup level effects.
simData

Large example, heterogeneous data, group, subgroup, and individual level effects.
setupBaseSyntax

Set up base syntax file.
ts

Small example, heterogeneous data, group and individual level effects
w2e

Create edge list from weight matrix.
return.zs

Returns z values from lavaan fit object.
setupPrepPaths

Allows user to open and close certain paths.
setupTransformData

Transform raw data as required.
create.tree

Create structure of group search solutions.
aggSEM

Group-level structural equation model search.
batch.create.tree

Create tree structures for group search solutions.
determine.subgroups

Determines subgroups.
count.excellent

Counts number of excellent fit indices
get.params

Grabs final coefficients for each individual.
HRFsim

Hemodynamic Response Function (HRF) GIMME example.
convolve

Group iterative multiple model estimation.
fit.model

Attempt to fit lavaan model.
lowest.z

Identifies lowest z value from list of z values.
gimme-package

Group iterative multiple model estimation
expand.grid.unique

Provides unique combinations of two vectors.
final.org

Wrapup, create output files.