data("YouthGratitude", package = "psychotools")
summary(YouthGratitude)
## modeling can be carried out using package lavaan
## Not run:
# ## remove cases with 'imputed' values (not in 1, ..., 9)
# yg <- YouthGratitude[apply(YouthGratitude[, 4:28], 1, function(x) all(x
#
# ## GQ-6
# gq6_congeneric <- cfa(
# 'f1 =~ gq6_1 + gq6_2 + gq6_3 + gq6_4 + gq6_5',
# data = yg, group = "agegroup", meanstructure = TRUE)
# gq6_tauequivalent <- cfa(
# 'f1 =~ gq6_1 + gq6_2 + gq6_3 + gq6_4 + gq6_5',
# data = yg, group = "agegroup", meanstructure = TRUE,
# group.equal = "loadings")
# gq6_parallel <- cfa(
# 'f1 =~ gq6_1 + gq6_2 + gq6_3 + gq6_4 + gq6_5',
# data = yg, group = "agegroup", meanstructure = TRUE,
# group.equal = c("loadings", "residuals", "lv.variances"))
# anova(gq6_congeneric, gq6_tauequivalent, gq6_parallel)
# t(sapply(
# list(gq6_congeneric, gq6_tauequivalent, gq6_parallel),
# function(m) fitMeasures(m)[c("chisq", "df", "cfi", "srmr")]
# ))
#
# ## GAC
# gac_congeneric <- cfa(
# 'f1 =~ gac_1 + gac_2 + gac_3',
# data = yg, group = "agegroup", meanstructure = TRUE)
# gac_tauequivalent <- cfa(
# 'f1 =~ gac_1 + gac_2 + gac_3',
# data = yg, group = "agegroup", meanstructure = TRUE,
# group.equal = "loadings")
# gac_parallel <- cfa(
# 'f1 =~ gac_1 + gac_2 + gac_3',
# data = yg, group = "agegroup", meanstructure = TRUE,
# group.equal = c("loadings", "residuals", "lv.variances"))
# anova(gac_congeneric, gac_tauequivalent, gac_parallel)
# t(sapply(
# list(gac_congeneric, gac_tauequivalent, gac_parallel),
# function(m) fitMeasures(m)[c("chisq", "df", "cfi", "srmr")]
# ))
#
# ## GRAT
# grat_congeneric <- cfa(
# 'f1 =~ losd_2 + losd_3 + losd_4 + losd_5 + losd_6
# f2 =~ sa_1 + sa_2 + sa_3 + sa_4 + sa_5 + sa_6
# f3 =~ ao_1 + ao_2 + ao_3 + ao_4',
# data = yg, group = "agegroup", meanstructure = TRUE)
# grat_tauequivalent <- cfa(
# 'f1 =~ losd_2 + losd_3 + losd_4 + losd_5 + losd_6
# f2 =~ sa_1 + sa_2 + sa_3 + sa_4 + sa_5 + sa_6
# f3 =~ ao_1 + ao_2 + ao_3 + ao_4',
# data = yg, group = "agegroup", meanstructure = TRUE,
# group.equal = "loadings")
# grat_parallel <- cfa(
# 'f1 =~ losd_2 + losd_3 + losd_4 + losd_5 + losd_6
# f2 =~ sa_1 + sa_2 + sa_3 + sa_4 + sa_5 + sa_6
# f3 =~ ao_1 + ao_2 + ao_3 + ao_4',
# data = yg, group = "agegroup", meanstructure = TRUE,
# group.equal = c("loadings", "residuals", "lv.variances"))
# anova(grat_congeneric, grat_tauequivalent, grat_parallel)
# t(sapply(
# list(grat_congeneric, grat_tauequivalent, grat_parallel),
# function(m) fitMeasures(m)[c("chisq", "df", "cfi", "srmr")]
# ))
# ## End(Not run)
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