Adds a warning to the r2mlm_ci() function above low coverage.
Addresses an issue in r2mlm3_manual() to make input match
documentation.
r2mlm 0.3.7
Major Changes
Add confidence interval functionality for two-level models using
Mark Lai’s bootmlm package: Lai, M.H.C. (2021). Bootstrap Confidence
Intervals for Multilevel Standardized Effect Size. Multivariate
Behavioural Research, 56(4), 558-578. This only works with the automatic
r2mlm() function and lme4 because bootmlm requires a fitted merMod
object from lmer.
Minor Edits
Edited formatting of r2mlm_manual() and r2mlm_comp_manual()
documentation to make the examples easier to read.
r2mlm 0.3.5
Minor Edits
Added internal function to print citation on attachment.
Rockchalk fixed, so adding it back as a dependency.
r2mlm 0.3.4
Minor Edits
Replaces rockchalk dependency with misty v. 0.4.12.
r2mlm 0.3.3
Minor Edits
Fixes typo in r2mlm3_manual (#59).
Fixes typo in r2mlm3_manual (#62).
r2mlm 0.3.2
Major Changes
Output now returns as numeric rather than characters. (#55)
Minor Edits
Removes broomExtra dependency. (#52, #57)
Changes how variable types are checked from if() to is().
r2mlm 0.3.1
Major Changes
Exported r2mlm_long_manual to be user-facing.
Minor Edits
Updated r2mlm_manual and r2mlm_comp_manual
documentation to reflect changes to teachsat dataset
implemented in version 0.3.0. (#53)
r2mlm 0.3.0
Major Changes
Adds two manual functions: one for 3-level models (r2mlm3_manual)
and one for models with heteroscedasticity, autocorrelation,
nonlinearity, and non-centered-within-cluster models
(r2mlm_long_manual)
Bar graph output is now optional. The default behaviour is to output
bar graphs, but if you don’t want graphical output, the argument is
bargraph = FALSE. For example,
r2mlm(model, bargraph = FALSE). (Issue #46)
Bug Fixes
To test whether clusters are mean-centered, the code computes
cluster means for all level-1 variables, sees if the means are roughly
zero (< .0000001), and if yes then it assigns
clustermeancentered = TRUE. This update changes the code to
test whether the absolute value of the means are roughly zero,
to address the case in which a cluster has a negative non-zero mean
(that would otherwise mistakenly be assigned to
clustermeancentered = TRUE because the negative number is
less than 0.0000001). (Issue #41)
Fixes an issue where models with non-cwc interaction terms were
returning results as though they were centered-within-cluster. r2mlm
returns non-cwc results, r2mlm_comp breaks. (Issue #42)
Fixed an error thrown if certain groups only have one unit: “Error
in if (variance_tracker == 0) { : missing value where TRUE/FALSE
needed.” Fixed this (#44).
Minor Edits
Changed simulated data
r2mlm 0.2.0
Major Changes
Can now accept data with missing points, handles it with listwise
deletion via broomExtra::augment(model). (#23, #29)
Related to accepting missing data (#23, #29), this update changes
r2mlm_comp() to accept optional data argument. You can now
call r2mlm_comp(modelA, modelB) or
r2mlm_comp(modelA, modelB, data). If data is provided, the
function will use that data. If data is not provided and models are
hierarchically nested, the function will extract data automatically. If
data is not provided and models are not hierarchically nested, the
function will throw an error asking users to input data.
Bug Fixes
Bug fix: when groups of 1 exist, variance was returning as NA,
generating “Error in if (variance_tracker == 0) { : missing value where
TRUE/FALSE needed” (#26)
Minor Edits
Fixed typo in r2mlm_manual() documentation (#33)
Updates documentation of r2mlm() and
r2mlm_comp() to note that models run in lme4
must be formatted with random effects at the end of the formula.
(#30)
Refactored to increase modularity, adding files: utils.R,
prepare_data.R