Ease of use wrapper function for fitting various growth models specified by growthSS

Ease of use wrapper function for fitting various growth models specified by growthSS

Usage

fitGrowth(ss, ...)

Arguments

ss

A list generated by growthSS.

...

Additional arguments passed to model fitting functions determined by ss$type. For type = "nlme" these are passed to nlme::nlmeControl, not nlme::nlme. Additional arguments are documented in fitGrowthbrms, fitGrowthnlme, fitGrowthnls, fitGrowthnlrq, fitGrowthmgcvgam, fitGrowthsurvreg, fitGrowthflexsurv.

Value

A fit model from the selected type.

See also

growthPlot for model visualization, testGrowth for hypothesis testing, barg for Bayesian model reporting metrics.

Examples

simdf <- growthSim("logistic",
  n = 20, t = 25,
  params = list("A" = c(200, 160), "B" = c(13, 11), "C" = c(3, 3.5))
)
ss <- growthSS(
  model = "logistic", form = y ~ time | group,
  df = simdf, type = "nls"
)
fitGrowth(ss)
#> Nonlinear regression model
#>   model: y ~ A[group]/(1 + exp((B[group] - time)/C[group]))
#>    data: ss[["df"]]
#>      A1      A2      B1      B2      C1      C2 
#> 200.867 158.675  13.152  10.508   2.957   3.657 
#>  residual sum-of-squares: 308487
#> 
#> Number of iterations to convergence: 3 
#> Achieved convergence tolerance: 7.032e-06
ss <- growthSS(
  model = "gam", form = y ~ time | group,
  df = simdf, type = "nls"
)
fitGrowth(ss)
#> 
#> Call:
#> stats::lm(formula = ss[["formula"]], data = ss[["df"]])
#> 
#> Coefficients:
#>      (Intercept)         bs(time)1         bs(time)2         bs(time)3  
#>           9.1722          -51.3695          228.1606          183.3481  
#>           groupb  bs(time)1:groupb  bs(time)2:groupb  bs(time)3:groupb  
#>          -0.4303           77.2199          -52.0667          -41.4705  
#>