psychotools (version 0.2-0)

YouthGratitude: Measuring Gratitude in Youth

Description

Cross-section data on several gratitude scales for children and adolescents.

Usage

data("YouthGratitude")

source

Provided by Jeff Froh and Jinyan Fan.

Details

The gratitude scales employed are: GRAT: Gratitude, Resentment, Appreciation Test (1--9). Short form with subscales LOSD (lack of a sense of deprivation), SA (simple appreciation), and AO (appreciation for others). GQ-6: Gratitude Questionnaire-6 (1--7). GAC: Gratitude Adjective Checklist (1--5).

The item losd_1 has been omitted from all analyses in Froh et al. (2011) because it loaded lowly on all factors. Hence losd_1 is not listed in Table B1 of Froh et al. (2011). Instead, the remaining items are labeled losd_1 to losd_5.

References

Froh JJ, Fan J, Emmons RA, Bono G, Huebner ES, Watkins P (2011). Measuring Gratitude in Youth: Assessing the Psychometric Properties of Adult Gratitude Scales in Children and Adolescents. Psychological Assessment, 23(2), 311--324.

Examples

data("YouthGratitude", package = "psychotools")
summary(YouthGratitude)

## modeling can be carried out using package lavaan
## 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")]
))