psem is used to unite a list of structural equations into a single
structural equation model.
psem(...)A list of structural equations
Returns an object of class psem
psem takes a list of structural equations, which can be model objects
of classes: lm, glm, gls, pgls, Sarlm, lme, glmmPQL, lmerMod,
lmerModLmerTest, glmerMod, glmmTMB, gam.
It also takes objects of class formula, formula.cerror, corresponding
to additional variables to be included in the tests of directed separation
(X ~ 1) or correlated errors (X1 %~~% X2).
The function optionally accepts data objects of classes: matrix,
data.frame, SpatialPointsDataFrame, comparative.data, or these are derived
internally from the structural equations.
mod <- psem(
lm(rich ~ cover, data = keeley),
lm(cover ~ firesev, data = keeley),
lm(firesev ~ age, data = keeley),
data = keeley
)
summary(mod)
#>
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#>
#> Structural Equation Model of mod
#>
#> Call:
#> rich ~ cover
#> cover ~ firesev
#> firesev ~ age
#>
#> AIC
#> 1103.492
#>
#> ---
#> Tests of directed separation:
#>
#> Independ.Claim Test.Type DF Crit.Value P.Value
#> cover ~ age + ... coef 87 -1.8018 0.0750
#> rich ~ age + ... coef 87 -2.0146 0.0470 *
#> rich ~ firesev + ... coef 86 -1.9546 0.0539
#>
#> --
#> Global goodness-of-fit:
#>
#> Chi-Squared = 11.313 with P-value = 0.01 and on 3 degrees of freedom
#> Fisher's C = 17.136 with P-value = 0.009 and on 6 degrees of freedom
#>
#> ---
#> Coefficients:
#>
#> Response Predictor Estimate Std.Error DF Crit.Value P.Value Std.Estimate
#> rich cover 15.6727 4.7931 88 3.2698 0.0015 0.3291 **
#> cover firesev -0.0839 0.0184 88 -4.5594 0.0000 -0.4371 ***
#> firesev age 0.0597 0.0125 88 4.7781 0.0000 0.4539 ***
#>
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
#>
#> ---
#> Individual R-squared:
#>
#> Response method R.squared
#> rich none 0.11
#> cover none 0.19
#> firesev none 0.21