bplm {scan} | R Documentation |
Bayesian Piecewise Linear Model
Description
Computes a bayesian (hierarchical) piecewise linear model based on a Markov chain Monte Carlo sampler.
Usage
bplm(
data,
dvar,
pvar,
mvar,
model = c("W", "H-M", "B&L-B"),
contrast_level = c("first", "preceding"),
contrast_slope = c("first", "preceding"),
trend = TRUE,
level = TRUE,
slope = TRUE,
random_trend = FALSE,
random_level = FALSE,
random_slope = FALSE,
fixed = NULL,
random = NULL,
update_fixed = NULL,
...
)
## S3 method for class 'sc_bplm'
print(x, digits = 3, ...)
## S3 method for class 'sc_bplm'
export(
object,
caption = NA,
footnote = NA,
filename = NA,
round = 2,
nice = TRUE,
...
)
Arguments
data |
A single-case data frame. See |
dvar |
Character string with the name of the dependent 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. |
mvar |
Character string with the name of the measurement time variable. Defaults to the attributes in the scdf file. |
model |
Model used for calculating the dummy parameters (see Huitema &
McKean, 2000). Default is |
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. |
random_trend |
If TRUE, includes a random trend effect. |
random_level |
If TRUE, includes a random level effect. |
random_slope |
If TRUE, includes a random slope effect. |
fixed |
A formula that overwrites the automatically created fixed part of the regression model that 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 L1 or L2 variables into the regression model. |
random |
A formula that overwrites the automatically created random part of the regression model. |
update_fixed |
An easier way to change the fixed model part (e.g., |
... |
Further arguments passed to the mcmcglmm function. |
x |
An object returned by |
digits |
The minimum number of significant digits to be use. If set to "auto" (default), values are predefined. |
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. |
round |
Integer passed to the digits argument used to round values. |
nice |
If set TRUE (default) output values are rounded and optimized for publication tables. |
Value
An object of class sc_bplm
.
model | List containing information about the applied model. |
N | Number of single-cases. |
formula | A list containing the fixed and the random formulas of the hplm model. |
mcmglmm | Object of class MCMglmm. |
contrast | List with contrast definitions. |
Functions
-
print(sc_bplm)
: Print results -
export(sc_bplm)
: Export results as html table (seeexport()
)
Author(s)
Juergen Wilbert
See Also
Other regression functions:
autocorr()
,
corrected_tau()
,
hplm()
,
mplm()
,
plm()
,
trend()
Examples
# plm regression
bplm(example_A24)
# Multilevel plm regression with random intercept
bplm(exampleAB_50, nitt = 5000)
# Adding a random slope
bplm(exampleAB_50, random_level = TRUE, nitt = 5000)