-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy path7.lcaMplus.R
130 lines (113 loc) · 7.5 KB
/
7.lcaMplus.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
library(MplusAutomation)
library(gridExtra)
ISC_lvRlca <- ISC_lvR %>%
dplyr::select(all_of(Id), all_of(sampleID), all_of(Scales), all_of(Scalesb), all_of(Man_cate), all_of(Man_cont))
load("LCA_MplusModels.RData")
#------------Results with 5 classes by cycle
#----C1
MAllScalesbycyclec1cl5Mplus <- MAllScalesBycycleMplus$Mplus.lca_c1cl5.out$parameters$probability.scale %>%
rename_with(~ c("Class", "value")[which(c("LatentClass", "est") == .x)], .cols = c("LatentClass", "est")) %>%
mutate_at( c("param", "category", "Class"), ~ as.factor(.x))
#graphclass(MAllScalesbycyclec1cl5Mplus, nclass = 5)
MAllScalesbycyclec1cl5Mplus$Class <- factor(MAllScalesbycyclec1cl5Mplus$Class,
levels = c("2", "3", "4", "5", "1"),
labels =
c("Strongly agree \nwith all", "Agree all",
"Strongly agree \nwith Gender",
"Agree but no \nwith political",
"Disagree all"))
graphclass(MAllScalesbycyclec1cl5Mplus, nclass = 5, title = "Mplus Results - LCA 1999 with 5 classes")
#----C2
MAllScalesbycyclec2cl5Mplus <- MAllScalesBycycleMplus$Mplus.lca_c2cl5.out$parameters$probability.scale %>%
rename_with(~ c("Class", "value")[which(c("LatentClass", "est") == .x)], .cols = c("LatentClass", "est")) %>%
mutate_at( c("param", "category", "Class"), ~ as.factor(.x))
#graphclass(MAllScalesbycyclec2cl5Mplus, nclass = 5)
MAllScalesbycyclec2cl5Mplus$Class <- factor(MAllScalesbycyclec2cl5Mplus$Class,
levels = c("4", "3", "2", "5", "1"), labels =
c("Strongly agree \nwith all", "Agree all",
"Strongly agree \nwith Gender",
"Agree but no \nwith political",
"Disagree all"))
graphclass(MAllScalesbycyclec2cl5Mplus, nclass = 5, title = "Mplus Results - LCA 2009 with 5 classes")
#----C3
MAllScalesbycyclec3cl5Mplus <- MAllScalesBycycleMplus$Mplus.lca_c3cl5.out$parameters$probability.scale %>%
rename_with(~ c("Class", "value")[which(c("LatentClass", "est") == .x)], .cols = c("LatentClass", "est")) %>%
mutate_at( c("param", "category", "Class"), ~ as.factor(.x))
#graphclass(MAllScalesbycyclec3cl5Mplus, nclass = 5)
MAllScalesbycyclec3cl5Mplus$Class <- factor(MAllScalesbycyclec3cl5Mplus$Class,
levels = c("4", "5", "1", "3", "2"), labels =
c("Strongly agree \nwith all", "Agree all",
"Strongly agree \nwith Gender",
"Agree but no \nwith political",
"Disagree all"))
graphclass(MAllScalesbycyclec3cl5Mplus, nclass = 5, title = "Mplus Results - LCA 2016 with 5 classes")
#Mplus
#--Model fit
Graph_modelfit <- function(Modellist){
resultsbyallo <- SummaryTable(eval(parse(text=paste0(Modellist))),
keepCols = c("Title", "Observations", "NLatentClasses", "NDependentVars", "Parameters", "LL",
"AIC", "BIC", "aBIC", "Entropy", "AICC"), sortBy = "BIC") #type = "html"
resultsbyallo$cycle <- str_remove(resultsbyallo$Title, " with [1-9] classes;")
resultsbyallo$cycle <- str_remove(resultsbyallo$cycle, "LCA ")
resultsbyall<-tidyr::gather(resultsbyallo, "Fit", "Value", 6:11)
fit.plot <- ggplot(resultsbyall) +
geom_point(aes(x = factor(NLatentClasses), y = Value), size=3) +
geom_line(aes(factor(NLatentClasses), Value, group = 1)) +
theme_bw()+
labs(x = "NClasses", y="", title = "Model fit for all scales") +
facet_grid(Fit ~ cycle , scales = "free")
print(fit.plot)
}
Graph_modelfit("MAllScalesBycycleMplus")
# compareModels(MAllScalesBycycleMplus$Mplus.lca_c1cl4.out,
# MAllScalesBycycleMplus$Mplus.lca_c1cl5.out, diffTest = TRUE)
# compareModels(MAllScalesBycycleMplus$Mplus.lca_c2cl4.out,
# MAllScalesBycycleMplus$Mplus.lca_c2cl5.out, diffTest = TRUE)
# compareModels(MAllScalesBycycleMplus$Mplus.lca_c3cl4.out,
# MAllScalesBycycleMplus$Mplus.lca_c3cl5.out, diffTest = TRUE)
# MeansBycycle <- rbind(cbind(Cycle = "C1", MAllScalesBycycleMplus$Mplus.lca_c1cl5.out$parameters$unstandardized %>%
# filter(paramHeader == "Means")),
# cbind(Cycle = "C2", MAllScalesBycycleMplus$Mplus.lca_c2cl5.out$parameters$unstandardized %>%
# filter(paramHeader == "Means")),
# cbind(Cycle = "C3", MAllScalesBycycleMplus$Mplus.lca_c3cl5.out$parameters$unstandardized %>%
# filter(paramHeader == "Means"))) %>% dplyr::select(-paramHeader,-LatentClass) %>%
# knitr::kable(caption = "Means")
# MeansBycycle
# c1 c("2", "3", "4", "5", "1")
# c("Strongly agree \nwith all", "Agree all",
# "Strongly agree \nwith Gender",
# "Agree but no \nwith political",
# "Disagree all")
# c2 c("4", "3", "2", "5", "1")
# c3 c("4", "5", "1", "3", "2")
modelEstimated_Bycycle <- left_join(left_join(MAllScalesBycycleMplus$Mplus.lca_c1cl5.out$class_counts$modelEstimated %>%
rename_with(~ c("count C1", "prop C1")[which(c("count", "proportion") == .x)], .cols = c("count", "proportion")) %>%
mutate(class =
case_when(
class == 2 ~ "Strongly agree with all",
class == 3 ~ "Agree all",
class == 4 ~ "Strongly agree with Gender",
class == 5 ~ "Agree but no with political",
class == 1 ~ "Disagree all")),
MAllScalesBycycleMplus$Mplus.lca_c2cl5.out$class_counts$modelEstimated %>%
rename_with(~ c("count C2", "prop C2")[which(c("count", "proportion") == .x)], .cols = c("count", "proportion")) %>%
mutate(class =
case_when(
class == 4 ~ "Strongly agree with all",
class == 3 ~ "Agree all",
class == 2 ~ "Strongly agree with Gender",
class == 5 ~ "Agree but no with political",
class == 1 ~ "Disagree all")), by = "class"),
MAllScalesBycycleMplus$Mplus.lca_c3cl5.out$class_counts$modelEstimated %>%
rename_with(~ c("count C3", "prop C3")[which(c("count", "proportion") == .x)], .cols = c("count", "proportion")) %>%
mutate(class =
case_when(
class == 4 ~ "Strongly agree with all",
class == 5 ~ "Agree all",
class == 1 ~ "Strongly agree with Gender",
class == 3 ~ "Agree but no with political",
class == 2 ~ "Disagree all")), by = "class") %>%
knitr::kable(caption = "Class counts")
modelEstimated_Bycycle
SummaryTable(MAllScalesAllcycleMplus)
SummaryTable(MByScalesAllcycleMplus)