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Random-effect BLUPs (conditional modes) for a freqTLS fit

Source: R/methods.R
ranef.Rd

ranef() returns the predicted random intercepts (the conditional modes / BLUPs) with their conditional standard errors, for a fit with a random intercept on any of CTmax, log_z, low, or log_k (<param> ~ <fixed> + (1 | group)). It errors for a fixed-effects-only fit. Each BLUP is a deviation on its coordinate's internal scale: CTmax in degrees C, log_z on log(z), low on logit(low), log_k on log(k). When several REs are present the rows are stacked in CTmax, log_z, low, log_k order.

Usage

ranef(object, ...)

# S3 method for class 'profile_tls'
ranef(object, ...)

Arguments

object

A profile_tls fit from fit_tls() with a random intercept.

...

Reserved; must be empty.

Value

A tibble with one row per group level (per RE term): group, term ("CTmax", "log_z", "low", or "log_k"), estimate (the BLUP), and std.error (the conditional SE).

Examples

d <- simulate_tls(family = "binomial", CTmax = 36, z = 4,
                  re_sd = 1.5, n_re_groups = 12, seed = 42)
fit <- fit_tls(
  tls_bf(survived | trials(total) ~ time(duration) + temp(temp),
         CTmax ~ 1 + (1 | colony)),
  data = d, family = "binomial", tref = 1)
ranef(fit)
#> # A tibble: 12 × 4
#>    group term  estimate std.error
#>    <chr> <chr>    <dbl>     <dbl>
#>  1 g1    CTmax    1.00      0.398
#>  2 g10   CTmax   -1.34      0.398
#>  3 g11   CTmax    0.780     0.398
#>  4 g12   CTmax    2.40      0.398
#>  5 g2    CTmax   -1.97      0.398
#>  6 g3    CTmax   -0.614     0.398
#>  7 g4    CTmax   -0.143     0.398
#>  8 g5    CTmax   -0.525     0.398
#>  9 g6    CTmax   -1.32      0.398
#> 10 g7    CTmax    1.06      0.398
#> 11 g8    CTmax   -1.27      0.398
#> 12 g9    CTmax    1.94      0.398