cnorm.betabinomial1: Fit a beta binomial regression model

View source: R/betaBinomial.R

cnorm.betabinomial1R Documentation

Fit a beta binomial regression model

Description

This function fits a beta binomial regression model where both the mean and standard deviation of the response variable are modeled as polynomial functions of the predictor variable. While 'cnorm-betabinomial2' fits a beta-binomial model on the basis of \gamma and \beta of a beta binomial function, this function fits \mu and \sigma, which are then used to estimate the beta binomial distribution parameters.

Usage

cnorm.betabinomial1(
  age,
  score,
  n = NULL,
  weights = NULL,
  mu = 3,
  sigma = 3,
  control = NULL,
  scale = "T",
  plot = T
)

Arguments

age

A numeric vector of predictor values (e.g., age).

score

A numeric vector of response values.

n

Number of items in the test, resp. maximum score to be achieved

weights

A numeric vector of weights for each observation. Default is NULL (equal weights).

mu

Integer specifying the degree of the polynomial for the mean model. Default is 2.

sigma

Integer specifying the degree of the polynomial for the standard deviation model. Default is 1.

control

A list of control parameters to be passed to the 'optim' function. If NULL, default values are used.

scale

type of norm scale, either T (default), IQ, z or percentile (= no transformation); a double vector with the mean and standard deviation can as well, be provided f. e. c(10, 3) for Wechsler scale index points

plot

Logical indicating whether to plot the model. Default is TRUE.

Details

The function standardizes the input variables, fits polynomial models for both the mean and standard deviation, and uses maximum likelihood estimation to find the optimal parameters. The optimization is performed using the BFGS method.

Value

A list of class "cnormBetaBinomial" containing:

beta_est

Estimated coefficients for the mean model

gamma_est

Estimated coefficients for the log-standard deviation model

se

Standard errors of the estimated coefficients

mu

Degree of the polynomial for the mean model

sigma

Degree of the polynomial for the standard deviation model

result

Full result from the optimization procedure


cNORM documentation built on Nov. 4, 2024, 5:07 p.m.