The hplm() function computes a hierarchical piecewise regression model.
hplm(
data,
dvar,
pvar,
mvar,
model = c("W", "H-M", "B&L-B", "JW"),
contrast = c("first", "preceding"),
contrast_level = NA,
contrast_slope = NA,
method = c("ML", "REML"),
control = list(opt = "optim"),
random.slopes = FALSE,
lr.test = FALSE,
ICC = TRUE,
trend = TRUE,
level = TRUE,
slope = TRUE,
random_trend = FALSE,
random_level = FALSE,
random_slope = FALSE,
fixed = NULL,
random = NULL,
update.fixed = NULL,
data.l2 = NULL,
...
)# S3 method for sc_hplm
print(x, digits = 3, smd = FALSE, casewise = FALSE, ...)
# S3 method for sc_hplm
export(
object,
caption = NA,
footnote = NA,
filename = NA,
kable_styling_options = list(),
kable_options = list(),
round = 2,
nice = TRUE,
casewise = FALSE,
...
)
# S3 method for sc_hplm
coef(object, casewise = FALSE, ...)
model | List containing infromation about the applied model. |
N | Number of single-cases. |
formula | A list containing the fixed and the random formulas of the hplm model. |
hplm | Object of class lme contaning the multilevel model. |
model.0 | Object of class lme containing the zero model. |
ICC | List containing intraclass correlation and test parameters. |
model.without | Object of class gls containing the fixed effect model. |
contrast | List with contrast definitions. |
A single-case data frame. See scdf() to learn about this
format.
Character string with the name of the dependent variable. Defaults to the attributes in the scdf file.
Character string with the name of the phase variable. Defaults to the attributes in the scdf file.
Character string with the name of the measurement time variable. Defaults to the attributes in the scdf file.
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".
Sets contrast_level and contrast_slope. Either "first", "preceding" or a contrast matrix.
Either "first", "preceding" or a contrast matrix. If NA contrast_level is a copy of contrast.
Either "first", "preceding" or a contrast matrix. If NA contrast_level is a copy of contrast.
Method used to fit your model. Pass "REML" to maximize the
restricted log-likelihood or "ML" for maximized log-likelihood. Default
is "ML".
A list of settings for the estimation algorithm, replacing the
default values passed to the function lmeControl of the nlme package.
If random.slopes = TRUE random slope effects of the
level, trend, and treatment parameter are estimated.
If set TRUE likelihood ratio tests are calculated comparing model with vs. without random slope parameters.
If ICC = TRUE an intraclass-correlation is estimated.
A logical indicating if a trend parameters is included in the model.
A logical indicating if a level parameters is included in the model.
A logical indicating if a slope parameters is included in the model.
If TRUE, includes a random trend trend effect.
If TRUE, includes a random level trend effect.
If TRUE, includes a random slope trend effect.
Defaults to the fixed part of 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.
The random part of the model.
An easier way to change the fixed model part
(e.g., . ~ . + newvariable).
A data frame providing additional variables at Level 2. The scdf File has to have names for all cases and the Level 2 data frame has to have a column named 'cases' with the names of the cases the Level 2 variables belong to.
Further arguments passed to the lme function.
An object returned by hplm()
The minimum number of significant digits to be use. If set to "auto" (default), values are predefined.
If TRUE, reports between-case standardized mean differences.
Returns the estimations for each case
An scdf or an object exported from a scan function.
Character string with table caption. If left NA (default) a caption will be created based on the exported object.
Character string with table footnote. If left NA (default) a footnote will be created based on the exported object.
String containing the file name. If a filename is given the output will be written to that file.
list with arguments passed to the kable_styling function.
list with arguments passed to the kable function.
Integer passed to the digits argument internally used to round values.
If set TRUE (default) output values are rounded and optimized for publication tables.
print(sc_hplm): Print results
export(sc_hplm): Export results as html table (see export())
coef(sc_hplm): Extract model coefficients
Juergen Wilbert
Other regression functions:
autocorr(),
bplm(),
corrected_tau(),
mplm(),
plm(),
trend()
## Compute hplm model on a MBD over fifty cases (restricted log-likelihood)
hplm(exampleAB_50, method = "REML", random.slopes = FALSE)
## Analyzing with additional L2 variables
Leidig2018 |>
add_l2(Leidig2018_l2) |>
hplm(update.fixed = .~. + gender + migration + ITRF_TOTAL*phaseB,
slope = FALSE, random.slopes = FALSE, lr.test = FALSE
)
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