Hierarchical piecewise linear model / piecewise regression

Description

The hplm function computes a hierarchical piecewise regression model.

Usage

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hplm(data, model = "B&L-B", method = "ML", control = list(opt = "optim"),
  random.slopes = TRUE, ICC = TRUE)

Arguments

data

A single-case data frame. See makeSCDF to learn about this format.

model

Regression model used for computation (see Huitema & McKean, 2000). Default is model = "B&L-B". Possible values are: "B&L-B", "H-M", "Mohr#1", "Mohr#2", and "Manly".

method

Method used to fit your model. Pass "REML" to maximize the restricted log-likelihood or "ML" for maximized log-likelihood. Default is "ML".

control

A list of settings for the estimation algorithm, replacing the default values passed to the function lmeControl of the nlme package.

random.slopes

If random.slopes = TRUE random slope effects of the level, trend, and treatment parameter are estimated.

ICC

If ICC = TRUE an intraclass-correlation is estimated.

Value

model

Character string from function call (see Arguments above).

method

Character string from function call (see Arguments above).

N

Number of single-cases.

analyze.random.slopes

Logical argument from function call (see Arguments above).

analyze.ICC

Logical argument from function call (see Arguments above).

random.trend.level

Linear mixed-effects model with random trend and level effect.

random.trend.slope

Linear mixed-effects model with random trend and slope effect.

random.level.slope

Linear mixed-effects model with random level and slope effect.

random.trend.level.slope

Linear mixed-effects model with random trend, level, and slope effect.

random.nointercept.trend.level.slope

Linear mixed-effects model with random trend, level, and slope effect without intercept.

random.trend

Significance test for random trend effect.

random.level

Significance test for random level effect.

random.slope

Significance test for random slope effect.

ICC

Intraclass correlation.

L.ICC

L ratio from intraclass correlation.

p.ICC

P-Value for intraclass correlation.

Author(s)

Juergen Wilbert

See Also

plm

Examples

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## Compute hpl model on a MBD over three cases (restricted log-likelihood)
dat <- rSC(3, MT = 30, B.start = 11, d.level = 1.0, d.slope = 0.05, d.trend = 0.05)
hplm(dat, method = "REML",random.slopes = FALSE)

## Use hplm with default settings
dat <- rSC(15, MT = 30, B.start = 11, d.level = 1.0, d.slope = runif(15,0,0.2), d.trend = 0.05)
hplm(dat)