
Summarize a TMB mixed-effects discounting fit
Source:R/dd-tmb-methods.R
summary.beezdiscounting_tmb.RdSummarize a TMB mixed-effects discounting fit
Arguments
- object
A
beezdiscounting_tmbobject.- report_space
Scale for the fixed-effect (
beta_k) estimates and standard errors in the coefficient table:"natural"(default;kon the natural scale viaexp()),"log10"(log10-k),"internal"or"log"(log-k, the estimation scale; the two coincide forbeta_k).statisticandp.valueare always computed on the estimation (log-k) scale regardless ofreport_space.- ...
Unused.
Value
An object of class "summary.beezdiscounting_tmb" with components:
call, model_class, backend, equation, family, coefficients,
variance_components, n_subjects, nobs, converged, logLik,
AIC, BIC, notes.
Examples
# \donttest{
dd <- simulate_dd_ip(n_subjects = 20, seed = 1)
fit <- fit_dd_tmb(dd, equation = "mazur", family = "sltb",
random_effects = k ~ 1, verbose = 0)
summary(fit)
#>
#> TMB Mixed-Effects Discounting Model Summary
#> ==================================================
#>
#> Call:
#> fit_dd_tmb(data = dd, equation = "mazur", family = "sltb", random_effects = k ~
#> 1, verbose = 0)
#>
#> Equation: mazur
#> Family: sltb
#> Backend: TMB_mixed
#> Convergence: Yes
#> Subjects: 20 Observations: 140
#>
#> --- Fixed Effects (k) ---
#> term estimate std.error statistic p.value
#> k:(Intercept) 0.0108 0.0015 -33.6239 <2e-16
#>
#> --- Variance Components ---
#> Component Estimate Scale
#> sigma_u (log10-k RE SD) 0.2309 log10
#> phi (precision) 12.4798 natural
#>
#> --- Fit Statistics ---
#> Log-likelihood: 198.92
#> AIC: -391.84 BIC: -383.01
summary(fit, report_space = "log10")
#>
#> TMB Mixed-Effects Discounting Model Summary
#> ==================================================
#>
#> Call:
#> fit_dd_tmb(data = dd, equation = "mazur", family = "sltb", random_effects = k ~
#> 1, verbose = 0)
#>
#> Equation: mazur
#> Family: sltb
#> Backend: TMB_mixed
#> Convergence: Yes
#> Subjects: 20 Observations: 140
#>
#> --- Fixed Effects (log10 k) ---
#> term estimate std.error statistic p.value
#> k:(Intercept) -1.9682 0.0585 -33.6239 <2e-16
#>
#> --- Variance Components ---
#> Component Estimate Scale
#> sigma_u (log10-k RE SD) 0.2309 log10
#> phi (precision) 12.4798 natural
#>
#> --- Fit Statistics ---
#> Log-likelihood: 198.92
#> AIC: -391.84 BIC: -383.01
# }