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Compute stability of effects across time

Source: R/longitudinal.R
srm_stability.Rd

Calculates correlations of actor (or partner) effects between consecutive time points, measuring how stable individual positions are over time.

Usage

srm_stability(object, type = c("actor", "partner"))

Arguments

object

An object of class srm with multiple time points.

type

One of "actor" or "partner".

Value

A data frame with columns: time1, time2, correlation, n. The correlation column is NA when fewer than 3 actors are shared between consecutive time points (Pearson correlation requires at least 3 observations).

Examples

# \donttest{
sim = sim_srm(n_actors = 10, n_time = 4, seed = 6886)
fit = srm(sim$Y)
srm_stability(fit, type = "actor")
#>   time1 time2 correlation  n
#> 1    t1    t2  0.06041908 10
#> 2    t2    t3  0.07972254 10
#> 3    t3    t4  0.43008139 10
# }