generate_four_param_pop_curve: Generates list containing values for each population-level...

In sciarraseb/nonlinSims: Generates longitudinal data sets according to a logistic pattern.

Generates list containing values for each population-level parameter.

Description

Four parameters (fixed effects) are used to characterize the logistic pattern and, due to the hierarchical nature of the to-be-generated data, each parameter has a corresponding value of variability (i.e., random-effect). The random effects are used to generate the covariance matrix. Note that correlations between random effects must also be set and that correlations between random effects and error variance at each time point are set to 0 by default (cor_param_error = 0). Internally, the function also assumes zero-value correlations between error variances at each time point The four parameters that characterize the logistic pattern of change take on the following meanings:

• theta: starting value (first plateau)

• alpha: ending value (second plateau)

• beta: amount of time to reach midway point (i.e., 50% of the distance between theta and alpha) from time = 0

• gamma: amount of time to reach satiation point (i.e., 73% of distance between theta and alpha) from midpoint

Usage

generate_four_param_pop_curve(
  theta_fixed,
  alpha_fixed,
  beta_fixed,
  gamma_fixed,
  sd_theta,
  sd_alpha,
  sd_beta,
  sd_gamma,
  sd_error,
  cor_alpha_theta = 0,
  cor_beta_theta = 0,
  cor_beta_alpha = 0,
  cor_gamma_theta = 0,
  cor_gamma_alpha = 0,
  cor_gamma_beta = 0,
  cor_param_error = 0
)

Arguments

sd_theta	standard deviation of first plateau
sd_alpha	standard deviation of second plateau
sd_gamma	standard deviation of gamma
sd_error	standard deviation of errors
cor_beta_theta	beta_theta correlation
cor_beta_alpha	beta_alpha correlation
cor_gamma_theta	gamma_theta correlation
cor_gamma_alpha	gamma_alpha correlation
cor_gamma_beta	gamma_beta-gamma correlation
cor_param_error	parameter-error correlation
num_time_points	number of time points
cor_theta_alpha	theta_alpha correlation
scaling_constant	constant that scales scores

Value

Returns a covariance matrix.

sciarraseb/nonlinSims documentation built on Jan. 30, 2023, 8:17 p.m.