20250717 - reorganization and placeholders

Author: isaactpetersen

hlm.Rmd

@@ -95,7 +95,9 @@ The following models are models that are fit in a linear mixed modeling framewor
 
 ## Growth Curve Models {#gcm}
 
-### Plot Observed Growth Curves
+### Linear Growth Curve Model {#linearGCM}
+
+#### Plot Observed Growth Curves
 
 ```{r}
 ggplot(
@@ -111,7 +113,7 @@ ggplot(
     name = "Math Score")
 ```
 
-### `lme4`
+#### `lme4`
 
 ```{r}
 linearMixedModel <- lmer(
@@ -124,7 +126,7 @@ linearMixedModel <- lmer(
 summary(linearMixedModel)
 ```
 
-#### Protoypical Growth Curve
+##### Protoypical Growth Curve
 
 ```{r}
 newData <- expand.grid(
@@ -155,7 +157,7 @@ ggplot(
   geom_line()
 ```
 
-#### Individuals' Growth Curves
+##### Individuals' Growth Curves
 
 ```{r}
 mydata$predictedValue <- predict(
@@ -172,7 +174,7 @@ ggplot(
   geom_line()
 ```
 
-#### Individuals' Trajectories Overlaid with Prototypical Trajectory
+##### Individuals' Trajectories Overlaid with Prototypical Trajectory
 
 ```{r}
 ggplot(
@@ -187,13 +189,13 @@ ggplot(
     linewidth = 2)
 ```
 
-#### Extract Random Effects {#extractRandomEffects}
+##### Extract Random Effects {#extractRandomEffects}
 
 ```{r}
 ranef(linearMixedModel)
 ```
 
-### `nlme`
+#### `nlme`
 
 ```{r}
 linearMixedModel_nlme <- lme(
@@ -206,13 +208,17 @@ linearMixedModel_nlme <- lme(
 summary(linearMixedModel_nlme)
 ```
 
-## Intraclass Correlation Coefficent {#icc}
+#### Intraclass Correlation Coefficent {#icc}
 
 ```{r}
 icc(linearMixedModel)
 icc(linearMixedModel_nlme)
 ```
 
+### Quadratic Growth Curve Model {#quadraticGCM}
+
+### Spline Growth Curve Model {#splineGCM}
+
 # Generalized Linear Mixed Models {#generalized}
 
 https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html (archived at https://perma.cc/9RFS-BCE7; source code: https://github.com/bbolker/mixedmodels-misc/blob/master/glmmFAQ.rmd)

sem.Rmd

@@ -102,9 +102,11 @@ ggplot(
 
 # Latent Growth Curve Model {#lgcm}
 
-## Model Syntax
+## Linear Model {#linearLGCM}
 
-### Abbreviated
+### Model Syntax
+
+#### Abbreviated
 
 ```{r}
 lgcm1_syntax <- '
@@ -124,7 +126,7 @@ lgcm1_syntax <- '
 '
 ```
 
-### Full
+#### Full
 
 ```{r}
 lgcm2_syntax <- '
@@ -154,9 +156,9 @@ lgcm2_syntax <- '
 '
 ```
 
-## Fit the Model
+### Fit the Model
 
-### Abbreviated
+#### Abbreviated
 
 ```{r}
 lgcm1_fit <- growth(
@@ -171,7 +173,7 @@ lgcm1_fit <- growth(
   em.h1.iter.max = 100000)
 ```
 
-### Full
+#### Full
 
 ```{r}
 lgcm2_fit <- sem(
@@ -184,9 +186,9 @@ lgcm2_fit <- sem(
   em.h1.iter.max = 100000)
 ```
 
-## Summary Output
+### Summary Output
 
-### Abbreviated
+#### Abbreviated
 
 ```{r}
 summary(
@@ -196,7 +198,7 @@ summary(
   rsquare = TRUE)
 ```
 
-### Full
+#### Full
 
 ```{r}
 summary(
@@ -206,7 +208,7 @@ summary(
   rsquare = TRUE)
 ```
 
-## Estimates of Model Fit
+### Estimates of Model Fit
 
 ```{r}
 fitMeasures(
@@ -220,29 +222,29 @@ fitMeasures(
     "rmsea.robust", "cfi.robust", "tli.robust"))
 ```
 
-## Residuals of Observed vs. Model-Implied Correlation Matrix
+### Residuals of Observed vs. Model-Implied Correlation Matrix
 
 ```{r}
 residuals(
   lgcm1_fit,
   type = "cor")
 ```
 
-## Modification Indices
+### Modification Indices
 
 ```{r}
 modificationindices(
   lgcm1_fit,
   sort. = TRUE)
 ```
 
-## Internal Consistency Reliability
+### Internal Consistency Reliability
 
 ```{r}
 compRelSEM(lgcm1_fit)
 ```
 
-## Path Diagram
+### Path Diagram
 
 ```{r}
 semPaths(
@@ -252,9 +254,9 @@ semPaths(
   edge.label.cex = 1.5)
 ```
 
-## Plot Trajectories
+### Plot Trajectories
 
-### Protoypical Growth Curve
+#### Protoypical Growth Curve
 
 Calculated from intercept and slope parameters:
 
@@ -299,7 +301,7 @@ ggplot(
   geom_line()
 ```
 
-### Individuals' Growth Curves
+#### Individuals' Growth Curves
 
 Calculated from intercept and slope parameters:
 
@@ -347,7 +349,7 @@ ggplot(
   geom_line()
 ```
 
-### Individuals' Trajectories Overlaid with Prototypical Trajectory
+#### Individuals' Trajectories Overlaid with Prototypical Trajectory
 
 ```{r}
 newData <- as.data.frame(predict(lgcm1_fit))
@@ -374,11 +376,11 @@ ggplot(
     linewidth = 2)
 ```
 
-# Latent Basis Growth Curve Model {#lbgcm}
+## Latent Basis Model {#latentBasisLGCM}
 
-## Model Syntax
+### Model Syntax
 
-### Abbreviated
+#### Abbreviated
 
 ```{r}
 lbgcm1_syntax <- '
@@ -398,7 +400,7 @@ lbgcm1_syntax <- '
 '
 ```
 
-### Full
+#### Full
 
 ```{r}
 lbgcm2_syntax <- '
@@ -428,9 +430,9 @@ lbgcm2_syntax <- '
 '
 ```
 
-## Fit the Model
+### Fit the Model
 
-### Abbreviated
+#### Abbreviated
 
 ```{r}
 lbgcm1_fit <- growth(
@@ -445,7 +447,7 @@ lbgcm1_fit <- growth(
   em.h1.iter.max = 100000)
 ```
 
-### Full
+#### Full
 
 ```{r}
 lbgcm2_fit <- sem(
@@ -458,9 +460,9 @@ lbgcm2_fit <- sem(
   em.h1.iter.max = 100000)
 ```
 
-## Summary Output
+### Summary Output
 
-### Abbreviated
+#### Abbreviated
 
 ```{r}
 summary(
@@ -470,7 +472,7 @@ summary(
   rsquare = TRUE)
 ```
 
-### Full
+#### Full
 
 ```{r}
 summary(
@@ -480,7 +482,7 @@ summary(
   rsquare = TRUE)
 ```
 
-## Estimates of Model Fit
+### Estimates of Model Fit
 
 ```{r}
 fitMeasures(
@@ -494,29 +496,29 @@ fitMeasures(
     "rmsea.robust", "cfi.robust", "tli.robust"))
 ```
 
-## Residuals of Observed vs. Model-Implied Correlation Matrix
+### Residuals of Observed vs. Model-Implied Correlation Matrix
 
 ```{r}
 residuals(
   lbgcm1_fit,
   type = "cor")
 ```
 
-## Modification Indices
+### Modification Indices
 
 ```{r}
 modificationindices(
   lbgcm1_fit,
   sort. = TRUE)
 ```
 
-## Internal Consistency Reliability
+### Internal Consistency Reliability
 
 ```{r}
 compRelSEM(lbgcm1_fit)
 ```
 
-## Path Diagram
+### Path Diagram
 
 ```{r}
 semPaths(
@@ -526,9 +528,9 @@ semPaths(
   edge.label.cex = 1.5)
 ```
 
-## Plot Trajectories
+### Plot Trajectories
 
-### Protoypical Growth Curve
+#### Protoypical Growth Curve
 
 ```{r}
 lbgcm1_intercept <- coef(lbgcm1_fit)["intercept~1"]
@@ -556,7 +558,7 @@ ggplot(
   geom_line()
 ```
 
-### Individuals' Growth Curves
+#### Individuals' Growth Curves
 
 ```{r}
 person_factors <- as.data.frame(predict(lbgcm1_fit))
@@ -593,30 +595,26 @@ ggplot(
   geom_line()
 ```
 
-### Individuals' Trajectories Overlaid with Prototypical Trajectory
-
-```{r}
-#ggplot(
-#  data = newData) +
-#  xlab("Timepoint") +
-#  ylab("Score") +
-#  scale_x_continuous(
-#    limits = c(0, 3),
-#    labels = 1:4) +
-#  scale_y_continuous(
-#    limits = c(-10, 20)) +
-#  geom_abline(
-#    mapping = aes(
-#      slope = slope,
-#      intercept = intercept)) +
-#  geom_abline(
-#    mapping = aes(
-#      slope = lgcm1_slope,
-#      intercept = lgcm1_intercept),
-#    color = "blue",
-#    linewidth = 2)
+#### Individuals' Trajectories Overlaid with Prototypical Trajectory
+
+```{r}
+ggplot() +
+  geom_line( # individuals' model-implied trajectories
+    data = individual_trajectories,
+    aes(x = time, y = value, group = id),
+  ) +
+  geom_line( # prototypical trajectory
+    data = newData,
+    aes(x = time, y = predictedValue),
+    color = "blue",
+    linewidth = 2
+  )
 ```
 
+## Quadratic Model {#quadraticLGCM}
+
+## Spline Model {#splineLGCM}
+
 # Latent Change Score Model {#lcsm}
 
 ## Model Syntax