mplm | R Documentation |
The mplm()
function computes a multivariate piecewise regression model.
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, ...)
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. |
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 |
contrast |
Sets contrast_level and contrast_slope. Either "first", "preceding" or a contrast matrix. |
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., |
update |
An easier way to change the regression formula (e.g., |
na.action |
Defines how to deal with missing values. |
... |
Further arguments passed to the |
x |
Object returned from |
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. |
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. |
print(sc_mplm)
: Print results
Juergen Wilbert
Other regression functions:
autocorr()
,
corrected_tau()
,
hplm()
,
plm()
,
trend()
res <- mplm(Leidig2018$`1a1`,
dvar = c("academic_engagement", "disruptive_behavior")
)
print(res)
## also report standardized coefficients:
print(res, std = TRUE)
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