print.summary.cbc_lm

Print method for 'summary.cbc_lm' objects. Prints the call used to create the
models, the mean coefficients, (optionally) the bootstrap mean coefficients,
bootstrap standard errors, bootstrap confidence intervals,
and the tidy and glance summaries for each model.

The 'OLStrajr' package provides comprehensive functions for ordinary
least squares (OLS) trajectory analysis and case-by-case OLS regression as
outlined in Carrig, Wirth, and Curran (2004) <doi:10.1207/S15328007SEM1101_9>
and Rogosa and Saner (1995) <doi:10.3102/10769986020002149>. It encompasses two
primary functions, OLStraj() and cbc_lm(). The OLStraj() function simplifies
the estimation of individual growth curves over time via OLS regression, with
options for visualizing both group-level and individual-level growth trajectories
and support for linear and quadratic models. The cbc_lm() function facilitates
case-by-case OLS estimates and provides unbiased mean population intercept and
slope estimators by averaging OLS intercepts and slopes across cases. It further
offers standard error calculations across bootstrap replicates and computation
of 95% confidence intervals based on empirical distributions from the resampling
processes.

Mackson Ncube

OLStrajr

Ordinary Least Squares Trajectory Analysis

mightymetrika, LLC 

print.summary.cbc_lm function

<dl><dt>x</dt>
<dd>A 'summary.cbc_lm' object.</dd>
<dt>digits</dt>
<dd>The number of significant digits to use when printing.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Print Method for 'summary.cbc_lm' Objects — print.summary.cbc_lm

<dl>

<dt>x</dt>
<dd>A 'summary.cbc_lm' object.</dd>


<dt>digits</dt>
<dd>The number of significant digits to use when printing.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

print.summary.cbc_lm: Print Method for 'summary.cbc_lm' Objects

Description

Usage

Value

Arguments

See Also