MuMIn from "Imports" to "Suggests" due to its unresolved CRAN issues which need fixing before 2024-06-14.file argument for EMMEANS() to allow for saving the contrast table to MS Word.var and items support more flexible input, e.g.:
.mean(var="X", items=1:3) matches X1, X2, X3.mean(var="X.{any_placeholder}.pre", items=1:3) matches X.1.pre, X.2.pre, X.3.pre\donttest{} in more examples to avoid unnecessary errors.cor_multilevel(): Multilevel correlations (within-level and between-level).pkg and value.labels for import(), providing more flexible settings and allowing for converting variables with value labels into R factors.Corr(): Now it uses ggplot2 to produce correlation plot.nsmall for all functions. Now always use digits instead. (Both were acceptable in former versions.)EMMEANS() output when "d" is used as a variable name.library(bruceR).packageStartupMessage() so that the messages can be suppressed.import() support for importing URL-source data files and no-extension files.paired.d.type argument for TTEST(): Allow for specifying 3 types of Cohen's d for paired-samples t-test ("dz", "dav", and "drm"). See Lakens (2013) for details.
"dz" (d for standardized difference)
$$\text{Cohen's } d_{z} = \frac{M_{diff}}{SD_{diff}}$$
"dav" (d for average standard deviation)
$$\text{Cohen's } d_{av} = \frac{M_{diff}}{\frac{SD_{1} + SD_{2}}{2}}$$
"drm" (d for repeated measures, corrected for correlation)
$$\text{Cohen's } d_{rm} = \frac{M_{diff} \times \sqrt{2(1 - r_{1,2})}}{\sqrt{SD_{1}^2 + SD_{2}^2 - 2 \times r_{1,2} \times SD_{1} \times SD_{2}}}$$
library(bruceR).add() and added(): Enhanced functions designed to create, modify, and/or delete variables. The functions combine the advantages of := (data.table), mutate() (dplyr), and transmute() (dplyr). See help page for the usage and convenience..sum() and .mean(): Tidy version of SUM() and MEAN() designed only for add() and added(). See help page for the usage and convenience.SUM(), MEAN(), EMMEANS().pkgdown. Configuration is specified in _pkgdown.yml.R CMD check workflow on GitHub, which checks the code for each push.cc(). Now it becomes much more convenient!MANOVA(): "Data are aggregated to mean (across items/trials) if there are >=2 observations per subject and cell. You may use Linear Mixed Model to analyze the data, e.g., with subjects and items as level-2 clusters."center argument for PROCESS() (default is TRUE) for users who want to turn off the automatic grand-mean centering. However, mean centering is still highly suggested if one aim to obtain "main effect" rather than "fixed effect" (note: a fixed effect is not necessarily a main effect).estimator argument for CFA() (default is "ML") for users who want to use any other estimator (fixed issue #17).cc(): Split up a string (with separators) into a character vector (whitespace around separator is trimmed). For example, cc("A 1 , B 2 ; C 3 | D 4 \t E 5") produces a vector of c("A 1", "B 2", "C 3", "D 4", "E 5"). The default separators include , ; | \n \t. Users may also specify a separator.Added a guideline and examples for creating interaction plots using the returned object of MANOVA() and EMMEANS(). You can save the returned object and use the emmeans::emmip() function to create an interaction plot (based on the fitted model and a formula specification). For usage, please see the help page of emmeans::emmip(). It returns an object of class ggplot, which can be easily modified and saved using ggplot2 syntax.
Added an explanation of the automatic grand-mean centering in PROCESS().
afex package would see an unusual error when using the EMMEANS() function (Error: $ operator is invalid for atomic vectors). So now afex is again a strong dependency of bruceR, such that it is automatically installed when installing bruceR.EMMEANS() (when model is null).PROCESS() when setting mod.type="3-way" for multilevel models.print_table().PROCESS() for models without "x-y" in mod.path (e.g., Model 7).set.wd() in an R Markdown file.bruceR when library(bruceR).phia::testInteractions() in the output of EMMEANS(). These tests produce identical results to those obtained with the SPSS GLM (/EMMEANS) syntax.Freq(): Now both vector and data frame can be used. For example, users may specify either Freq(data$variable) or Freq(data, "variable").GLM_summary() and HLM_summary().HLM_summary(): level2.predictors and vartypes.lmerTest, mediation, interactions, and lavaan are now strong dependencies such that they would be installed when installing bruceR. This also fixes an error when using PROCESS() without these packages installed.print_table().GLM_summary() and HLM_summary() when only one factor-type predictor with >= 3 levels is in a regression model. Other bugs in these two functions have also been fixed.PROCESS() when setting mod.path="all" in testing multilevel moderated mediation effects. Fixed another bug of CI output for direct effects when testing multilevel models.TTEST(): One-sample, independent-samples, and paired-samples t-test. Multiple dependent/independent variables can be tested simultaneously. It also tests the assumption of homogeneity of variance and allows users to determine whether variances are equal or not. Cohen's d and 95% CI are reported by default (see Details and Examples in its help page for an issue about the inconsistency in the results of 95% CI of Cohen's d between R packages). Bayes factor BF10 is also supported. Key results can be saved in APA format to MS Word.import() / export(): Import/export data from/to a file with the two tidy functions, relieving users of the burden of remembering lots of read_xxx() / write_xxx() functions. Many file formats are supported (especially .txt, .csv, .tsv, .psv, .xls, .xlsx, .sav, .dta, .rda, .rdata, and clipboard). Note that the two functions are inspired by rio::import() / rio::export() and have several modifications for more convenient use. Since this version, the package rio is no longer a strong dependency of bruceR and would not be loaded when loading bruceR.Improved MANOVA() and EMMEANS():
print_table().EMMEANS() adopts this reasonable approach. If one uses MANOVA() and EMMEANS() to conduct the same t-test as using the TTEST() function, the results will be identical. Indeed, the estimation methods of Cohen's d in t-tests are acknowledged. In computing pooled SD in ANOVAs, it uses (1) the square root of mean square error (MSE) for between-subjects designs and (2) the square root of mean variance of all paired differences of the residuals of repeated measures for within-subjects and mixed designs. In both situations, it extracts the lm object from the returned value of MANOVA(). Then, it mainly uses the sigma() and residuals() functions, respectively, to do these estimates. For source code, see R file on GitHub. Thus, the results of Cohen's d for designs with repeated measures are now different from those in bruceR old versions (< 0.8.0), which indeed used an inappropriate method to compute pooled SD in such designs.ss.type for MANOVA() to specify either Type-II or Type-III Sum of Square; (2) aov.include for MANOVA() and model.type for EMMEANS(), for details, see the help pages.Improved Alpha(): Now it directly uses psych::alpha() and psych::omega(), rather than jmv::reliability(), to perform reliability analysis. The format of result output has been changed and improved.
Improved EFA() (almost completely rewritten): Now it directly uses psych::principal() and psych::fa(), rather than jmv::efa(), to perform factor analysis (PCA or EFA). The format of result output has been changed and improved. MS Word output has been supported. A wrapper function PCA() has been added: EFA(..., method="pca").
Improved CFA() and lavaan_summary(): Now CFA() only uses the lavaan::cfa(), rather than jmv:cfa(), to build model, and then uses lavaan_summary() to present results. For lavaan_summary(), many bugs have been fixed, and the format of result table has been changed and improved. Both functions now support saving table to MS Word.
Package dependencies: Much fewer strong dependencies, for faster and more robust installation. Removed rio and jmv from dependencies. No longer load rio and psych when library(bruceR).
set_wd() for set.wd().print_table(): Fixed an issue of incorrect length of Chinese character output in print_table(). Between-column blanks are now 2 spaces (rather than 1 space) for a clearer presentation of table columns.lavaan_summary() and granger_test().digits parameter as the equivalent to the nsmall parameter for all relevant functions.mediation, interactions, MuMIn, and texreg are now SUGGESTS rather than IMPORTS.PROCESS().Corr().PROCESS(): PROCESS for mediation, moderation, and conditional process (moderated mediation) analyses! This function supports a total of 24 kinds of SPSS PROCESS models (Hayes, 2018) and also supports multilevel mediation/moderation analyses. Overall, it supports the most frequently used types of mediation, moderation, moderated moderation (3-way interaction), and moderated mediation (conditional indirect effect) analyses for (generalized) linear or linear mixed models. Regression model summary and effect estimates (simple slopes and/or indirect effects) are printed in an elegant way.lavaan_summary(): Tidy report of lavaan model.RANDBETWEEN() function.print_table() and other functions using print_table() inside: Describe(), Freq(), Corr(), MANOVA(), med_summary(), granger_causality().EMMEANS(): There is considerable disagreement on how to compute Cohen's d. Users should not take the default output as the only right results and are completely responsible for setting the "sd.pooled".model_summary(): (1) Model names with NULL; (2) Multicollinearity check results with NULL or other problems; (3) UTF-8 encoding problem in WPS software (no such problem in Microsoft Word).granger_causality(): Granger causality test (multivariate) based on vector autoregression (VAR) model. This function is an advanced and more general version of the function granger_test() (bivariate).set.wd(): Now it uses rstudioapi::getSourceEditorContext() to extract file path (even effective when running in R console), which only requires RStudio version >= 0.99.1111 and no longer has encoding problems (see release note in 0.6.1).theme_bruce(): Now it uses ggtext::element_markdown() to render Markdown/HTML rich text format, which can be used in plot text (e.g., titles).EMMEANS(): Now its results are always identical to those in SPSS (by setting model="multivariate" in emmeans::joint_tests() and emmeans::emmeans(), which use the lm or mlm objects rather than the aov object to perform tests). For a few cases with singular error matrix (i.e., some variables are linearly dependent), the results of simple-effect F tests will not be reported, but estimated marginal means and pairwise comparisons are not affected and so are still reported. Note that the EMMEANS results in old versions of bruceR (version < 0.6.0) were identical to SPSS, but version 0.6.0 deprecated the parameter repair and no longer set model$aov=NULL, which made the results not identical to SPSS (particularly for ANOVAs with repeated measures). In response to a user's feedback, now 0.6.2 has improved this function and makes its results accurate again.\code{\link[package:function]{package::function()}}.CFA() (for lavaan-style output).HLM_ICC_rWG(): Tidy report of HLM indices "ICC(1)" (non-independence of data), "ICC(2)" (reliability of group means), and "rWG"/"rWG(J)" (within-group agreement for single-item/multi-item measures).Run(): Run code parsed from text.show_colors(): Show multiple colors (or a palette) in a plot.%^%: Paste strings together (a wrapper of paste0()).set.wd(): Now it converts the extracted path string from "UTF-8" to "GBK" on Windows system to support paths including Chinese characters (otherwise, the path would become messy code and cause an error). Note that this problem does not exist on Mac OS. In addition, warning messages will be printed into the console if the user's RStudio version is lower than required (RStudio version >= 1.4.843 is required for a complete implementation of this function).Alpha(): Now it adds a parameter varrange (to keep the same as SUM(), MEAN(), ...) and reports both Cronbach's α and McDonald's ω, with more detailed documentation.Three ways to specify the variable list (implemented in the functions such as
SUM(),MEAN(),Alpha()):1.
var + items: use the common and unique parts of variable names. (e.g.,var="RSES", items=1:10, rev=c(3, 5, 8, 9, 10))2.
vars: directly define the variable list. (e.g.,vars=c("E1", "E2", "E3", "E4", "E5"), rev=c("E1", "E2"))3.
varrange: use the start and end positions of the variable list. (e.g.,varrange="E1:E5", rev=c("E1", "E2"))
Corr() (relevant to the changes in psych::corr.test() in a forthcoming release of the psych package).0 errors √ | 0 warnings √ | 0 notes √model_summary(): Tidy report of (single/multiple) regression models (into console or to a Word/HTML file; supporting most types of models; based on the texreg package).med_summary(): Tidy report of (simple/moderated) mediation analyses (based on the mediation package).ccf_plot(): Cross-correlation analysis (plotting with ggplot2).granger_test(): Granger test of predictive causality (based on the lmtest::grangertest() function).set.wd(), Describe(), Corr(), MANOVA(), and EMMEANS().library(bruceR).pkg_install_suggested() function).bruceR: BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.MANOVA() and EMMEANS(): ANOVA, simple-effect analyses, and multiple comparisons (based on the afex and emmeans packages).