mplm: Multivariate Piecewise linear model / piecewise regression

In scan: Single-Case Data Analyses for Single and Multiple Baseline Designs

Multivariate Piecewise linear model / piecewise regression

Description

The mplm() function computes a multivariate piecewise regression model. The function automatically creates the regression formula based on the provided data and the selected options. The default model includes trend, level, and slope effects for each dependent variable. The regression formula can be changed by providing a custom formula to the update argument.

Usage

mplm(
  data,
  dvar,
  mvar,
  pvar,
  model = c("W", "H-M", "B&L-B", "JW"),
  contrast = c("first", "preceding"),
  contrast_level = c(NA, "first", "preceding"),
  contrast_slope = c(NA, "first", "preceding"),
  trend = TRUE,
  level = TRUE,
  slope = TRUE,
  formula = NULL,
  update = NULL,
  na.action = na.omit,
  ...
)

## S3 method for class 'sc_mplm'
print(x, digits = "auto", std = FALSE, ...)

## S3 method for class 'sc_mplm'
export(
  object,
  caption = NA,
  footnote = NA,
  filename = NA,
  nice = TRUE,
  std = FALSE,
  decimals = 2,
  ...
)

Arguments

data	A single-case data frame. See scdf() to learn about this format.
dvar	Character string with the name of the dependent variable. Defaults to the attributes in the scdf file.
mvar	Character string with the name of the measurement time variable. Defaults to the attributes in the scdf file.
pvar	Character string with the name of the phase variable. Defaults to the attributes in the scdf file.
model	Model used for calculating the dummy parameters (see Huitema & McKean, 2000). Default is model = "W". Possible values are: "B&L-B", "H-M", "W", and deprecated "JW".
contrast	Sets contrast_level and contrast_slope. Either "first", "preceding" or a contrast matrix. If NA contrast is ignored.
contrast_level	Either "first", "preceding" or a contrast matrix. If NA contrast_level is a copy of contrast.
contrast_slope	Either "first", "preceding" or a contrast matrix. If NA contrast_level is a copy of contrast.
trend	A logical indicating if a trend parameters is included in the model.
level	A logical indicating if a level parameters is included in the model.
slope	A logical indicating if a slope parameters is included in the model.
formula	Defaults to the standard piecewise regression model. The parameter phase followed by the phase name (e.g., phaseB) indicates the level effect of the corresponding phase. The parameter 'inter' followed by the phase name (e.g., interB) adresses the slope effect based on the method provide in the model argument (e.g., "B&L-B"). The formula can be changed for example to include further variables into the regression model.
update	An easier way to change the regression formula (e.g., . ~ . + newvariable).
na.action	Defines how to deal with missing values.
...	Further arguments passed to the lm() function.
x	Object returned from mplm().
digits	The minimum number of significant digits to be use. If set to "auto" (default), values are predefined.
std	If TRUE, a table with standardized estimates is included.
object	An scdf or an object exported from a scan function.
caption	Character string with table caption. If left NA (default) a caption will be created based on the exported object.
footnote	Character string with table footnote. If left NA (default) a footnote will be created based on the exported object.
filename	String containing the file name. If a filename is given the output will be written to that file.
nice	If set TRUE (default) output values are rounded and optimized for publication tables.
decimals	Decimal places that are reported.

Details

The function currently only supports single-case data (i.e., one case per dataset). For multilevel piecewise regression models, please use the hplm function.

Value

model	Character string from function call (see arguments above).
contrast	List with contrast definitions.
full.model	Full regression model list.
formula	Formula of the mplm model.

Functions

• print(sc_mplm): Print results

• export(sc_mplm): Export results as html

Author(s)

Juergen Wilbert

See Also

Other regression functions: bplm(), fetch(), hplm(), plm(), print.sc_ac(), print.sc_bctau(), trend()

Examples

res <- mplm(Leidig2018$`1a1`,
  dvar = c("academic_engagement", "disruptive_behavior")
)
print(res)
## also report standardized coefficients:
print(res, std = TRUE)

scan documentation built on April 1, 2026, 9:06 a.m.