Lecture

You can find the lecture here

Some useful links:

• Structural Equation Modeling:

  • the Bible for SEM: Jon Lefcheck book

  • tutorial

• Check you model assumptions: performance package

  • package

  • tutorial

Example

rm(list = ls()) # Clean the workspace

#### > 1. Packages ####
# data handeling
library(dplyr)

# statistical analyses
library(performance)
library(lavaan)
library(piecewiseSEM)

#### > 2. Data simulations ####
# that is just creating a dataset to play with
n = 505 # number of observations
temperature = rep(seq(18, (0.05 * 100 + 18), 0.05),5)  # temperature data
water = 1.5 - 0.05 * temperature + rnorm(n, sd = 0.01) # water data 
plant = 10 + 0.5 * temperature + 20 * water + rnorm(n, sd = .1) # plant size

# merge in a data frame
df = data.frame(
  temperature,
  water,
  plant
)

#### > 3. data analyses ####

#### >> 3.1 data handling ####
#### >>> 3.1.1 check your data distribution ####
plot(df)

#### >>> 3.1.2 resale your data ####
df.1 = df %>%
  apply(., 2, scale) %>%
  data.frame()

plot(df.1)

#### >> 3.2 individual models ####
#### >>> 3.2.1 build your individual models ####
mod.plant = lm(formula = 'plant ~ temperature + water', 
               data = df.1)

mod.water = lm(formula = 'water ~ temperature',
               data = df.1)

#### >>> 3.2.2 check your individual models ####
check_model(mod.plant)

check_model(mod.water)

#### >>> 3.2.3 individual models fit ####
summary(mod.plant)

summary(mod.water)

#### >> 3.3 SEM fit ####
#### >>> 3.3.1 lavaan ####
model.lavaan = '
  plant ~ temperature + water
  water ~ temperature
'

fit.lavaan = sem(model = model.lavaan,
                 data = df.1)

#### >>> 3.3.2 piecewiseSEM ####
fit.piecewiseSEM = 
  psem(
    lm(formula = 'plant ~ temperature + water', 
       data = df.1),
    
    lm(formula = 'water ~ temperature',
       data = df.1)
    )

#### >> 3.4. SEM outputs ####
#### >> 3.4.1 lavaan outputs ####
summary(fit.lavaan)

#### >> 3.4.1 lavaan outputs ####
summary(fit.piecewiseSEM)
plot(fit.piecewiseSEM)

#### >> 3.5. fit quality ####
#### >> 3.5.1 lavaan ####
fitmeasures(fit.lavaan)

#### >> 3.5.2 piecewiseSEM ####
piecewiseSEM::fisherC(fit.piecewiseSEM)

#### >> 3.6. lavaan vs. piecewiseSEM output ####
summary(fit.lavaan, standardized = T)

coefs(fit.piecewiseSEM)