dataPrep: Reformat a user-provided dataframe in a generic form...

In ebmtnprof/qid: Version of "rties" to accompany "Quantifying Interpersonal Dynamics"

Description

In the dataframe, the partners within each dyad must have the same number of observations (e.g. rows of data), although those can include rows that have missing values (NAs). Each dyad, however, can have it's own unique number of observations.

Usage

dataPrep(basedata, id, dyad, obs, sysVar, dist, time_name,
  time_lag = NULL, coVar = NULL)

Arguments

basedata	A user-provided dataframe.
id	The name of the column in the dataframe that has the person-level identifier.
dyad	The name of the column in the dataframe that has the dyad-level identifier.
obs	The name of the column in the dataframe that has the time-varying observable (e.g., the variable for which dynamics will be assessed).
sysVar	The name of the column in the dataframe that has the system variable (e.g., something that will be predicted from the dynamics of the system).
dist	The name of the column in the dataframe that has a variable that distinguishes the partners (e.g., sex, mother/daughter, etc) that is numeric and scored 0/1.
time_name	The name of the column in the dataframe that indicates sequential temporal observations.
time_lag	An optional argument for the number of lags for the lagged observable.

Value

The function returns a dataframe that has all the variables needed for rties modeling, each renamed to a generic variable name, which are:

• id = person id

• dyad = dyad id

• obs = observed state variable

• sysVar = system variable

• dist1 = 0/1 variable where the 1's indicate the 1's in the original distinguishing variable

• time = the variable indicating temporal sequence

• dist0 = 0/1 variable where the 1's indicate the 0's in the original distinguishing variable

• obs_deTrend = the observed state variable with each person's linear trend removed

• p_ = all the same variables, but for a person's partner rather than themselves

ebmtnprof/qid documentation built on May 13, 2019, 6:08 p.m.