Summarizes (multiple) fitted generalized linear mixed models (odds ratios, ci, p-values...) as HTML table, or saves them as file. The fitted models may have different predictors, e.g. when comparing different stepwise fitted models.
sjt.glmer(..., pred.labels = NULL, depvar.labels = NULL, remove.estimates = NULL, group.pred = FALSE, exp.coef = TRUE, p.numeric = TRUE, emph.p = FALSE, p.zero = FALSE, separate.ci.col = TRUE, newline.ci = TRUE, show.ci = TRUE, show.se = FALSE, show.header = FALSE, show.col.header = TRUE, show.r2 = FALSE, show.icc = TRUE, show.re.var = TRUE, show.loglik = FALSE, show.aic = FALSE, show.aicc = FALSE, show.dev = TRUE, show.hoslem = FALSE, show.family = FALSE, string.pred = "Predictors", string.dv = "Dependent Variables", string.interc = "(Intercept)", string.obs = "Observations", string.est = NULL, string.ci = "CI", string.se = "std. Error", string.p = "p", ci.hyphen = " – ", digits.est = 2, digits.p = 3, digits.ci = 2, digits.se = 2, digits.summary = 3, cell.spacing = 0.2, cell.gpr.indent = 0.6, sep.column = TRUE, CSS = NULL, encoding = NULL, file = NULL, use.viewer = TRUE, no.output = FALSE, remove.spaces = TRUE)
... | One or more fitted generalized linear (mixed) models. |
---|---|
pred.labels | Character vector with labels of predictor variables.
If not |
depvar.labels | Character vector with labels of dependent variables of all fitted models. See 'Examples'. |
remove.estimates | Numeric vector with indices (order equals to row index of |
group.pred | Logical, if |
exp.coef | Logical, if |
p.numeric | Logical, if |
emph.p | Logical, if |
p.zero | logical, if |
separate.ci.col | Logical, if |
newline.ci | Logical, if |
show.ci | Logical, if |
show.se | Logical, if |
show.header | Logical, if |
show.col.header | Logical, if |
show.r2 | Logical, if |
show.icc | Logical, if |
show.re.var | Logical, if |
show.loglik | Logical, if |
show.aic | Logical, if |
show.aicc | Logical, if |
show.dev | Logical, if |
show.hoslem | Logical, if |
show.family | Logical, if |
string.pred | Character vector,used as headline for the predictor column.
Default is |
string.dv | Character vector, used as headline for the
dependent variable columns. Default is |
string.interc | Character vector, used as headline for the Intercept row.
Default is |
string.obs | character vector, used in the summary row for the count of observation
(cases). Default is |
string.est | Character vector, used for the column heading of estimates. |
string.ci | Character vector, used for the column heading of confidence interval values. Default is |
string.se | Character vector, used for the column heading of standard error values. Default is |
string.p | Character vector, used for the column heading of p values. Default is |
ci.hyphen | Character vector, indicating the hyphen for confidence interval range. May be an HTML entity. See 'Examples'. |
digits.est | Amount of decimals for table values. |
digits.p | Amount of decimals for p-values. |
digits.ci | Amount of decimals for confidence intervals. |
digits.se | Amount of decimals for standard error. |
digits.summary | Amount of decimals for values in model summary. |
cell.spacing | Numeric, inner padding of table cells. By default, this value is 0.2 (unit is cm), which is
suitable for viewing the table. Decrease this value (0.05 to 0.1) if you want to import the table
into Office documents. This is a convenient argument for the |
cell.gpr.indent | Indent for table rows with grouped factor predictors. Only applies
if |
sep.column | Logical, if |
CSS | A |
encoding | String, indicating the charset encoding used for variable and
value labels. Default is |
file | Destination file, if the output should be saved as file.
If |
use.viewer | Logical, if |
no.output | Logical, if |
remove.spaces | Logical, if |
Invisibly returns
the web page style sheet (page.style
),
the web page content (page.content
),
the complete html-output (page.complete
) and
the html-table with inline-css for use with knitr (knitr
)
for further use.
Computation of p-values (if necessary) is based on normal-distribution
assumption, treating the t-statistics as Wald z-statistics.
The variance components of the random effects (see show.re.var
) are
denoted like:
between-group-variance: tau-zero-zero
random-slope-intercept-correlation: rho-zero-one
Standard errors for generalized linear (mixed) models are not
the regular standard errors on the untransformed scale, as shown in the
summary()
-method. Rather, sjt.glmer()
uses adjustments
according to the delta method for approximating standard errors of
transformed regression parameters (see se
).