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 
#> 208.049 146.435  13.295  10.952   2.998   3.480 
#>  residual sum-of-squares: 172865
#> 
#> Number of iterations to convergence: 4 
#> Achieved convergence tolerance: 4.541e-08
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  
#>            9.615           -53.526           231.130           190.053  
#>           groupb  bs(time)1:groupb  bs(time)2:groupb  bs(time)3:groupb  
#>           -2.670            66.393           -63.155           -58.386  
#>