Summarize a panfmm fit
Usage
# S3 method for class 'panfmm'
summary(object, ...)Value
an object of class "summary.panfmm": a list with one
coefficient table per class (classes: estimate, standard error, z
value and p-value, ancillary parameter on the log scale), the table of
the class-probability (multinomial logit) parameters (prior), the mean
class probabilities, the class sizes by modal posterior class, and the
fit information (call, loglik, AIC, BIC, nobs, n_groups,
vcov_type).
See also
Other panfmm methods:
plot.panfmm(),
predict.panfmm(),
vcov.panfmm()
Examples
set.seed(3)
d <- data.frame(id = rep(1:150, each = 3), t = rep(1:3, 150), x = rnorm(450))
d$y <- rpois(450, exp(ifelse(rep(rbinom(150, 1, 0.4), each = 3) == 1, 1.5, 0) + 0.3 * d$x))
summary(panfmm(y ~ x, data = d, index = c("id", "t"), nstart = 2, seed = 1))
#>
#> Call:
#> panfmm(formula = y ~ x, data = d, index = c("id", "t"), nstart = 2,
#> seed = 1)
#>
#> Model: 2-class latent class Poisson model
#> n = 450 groups = 150 vcov: classical
#>
#> Class 1 (prior 0.621, 94 individuals by modal posterior, mean outcome 0.9923):
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) -0.04987 0.06919 -0.721 0.471
#> x 0.24535 0.05846 4.197 2.71e-05 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Class 2 (prior 0.379, 56 individuals by modal posterior, mean outcome 4.71):
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) 1.48145 0.04063 36.460 <2e-16 ***
#> x 0.32210 0.03908 8.241 <2e-16 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Class probabilities (multinomial logit, class 1 = reference):
#> Estimate Std. Error z value Pr(>|z|)
#> prior2:(Intercept) -0.4930 0.1758 -2.804 0.00504 **
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> logLik = -799.9038 df = 5 AIC = 1609.808 BIC = 1630.354
#>