Package: mariposa 0.7.4

mariposa: 'SPSS'-Compatible Statistical Tools for Survey Data

Statistical analysis of survey data with full support for survey weights, grouped operations, and 'tidyverse' integration. Provides 80 functions for data import/export ('SPSS', 'Stata', 'SAS', 'Excel') with label roundtripping and tagged NA preservation, label management (variable labels, value labels, type conversions, missing value declaration), data transformation (recoding, dummy coding, standardization, centering), descriptive statistics, codebook generation, hypothesis testing, correlation analysis, post-hoc comparisons, weighted statistics, scale analysis, regression, non-parametric tests, exact tests, factorial ANOVA, and ANCOVA. Every analysis offers compact print() and detailed summary() output with toggleable sections. Statistical results are validated against 'SPSS' version 29 within documented per-tier tolerances (see the compatibility vignette for per-function status). Methods follow the published algorithms of IBM Corp. (2023, "IBM SPSS Statistics Algorithms"), the Lilliefors-corrected normality test of Dallal and Wilkinson (1986) <doi:10.1080/00031305.1986.10475419>, and the adjusted standardized residuals of Haberman (1973) <doi:10.2307/2529686>. Designed for survey researchers, social scientists, and students working with complex survey designs.

Authors:Yannick Diehl [aut, cre]

mariposa_0.7.4.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mariposa/json (API)

# Install 'mariposa' in R:
install.packages('mariposa', repos = c('https://yannickdiehl.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yannickdiehl/mariposa/issues

Pkgdown/docs site:https://yannickdiehl.github.io

Datasets:

On CRAN:

Conda:

6.72 score 8 stars 58 downloads 82 exports 19 dependencies

Last updated from:10559813c2. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK268
source / vignettesOK341
linux-releaseOK287
macos-releaseOK314
macos-oldrelOK314
windows-develOK310
windows-releaseOK343
windows-oldrelOK382
wasm-releaseOK139

Exports:%>%ancovabinomial_testcenterchi_squarechisq_gofcodebookcopy_labelscramers_vcrosstabdescribedrop_labelsdunn_testefafactorial_anovafind_varfisher_testfrefrequencyfriedman_testgoodman_gammakendall_taukruskal_wallislevene_testlinear_regressionlogistic_regressionmann_whitneymarginal_effectsmcnemar_testmultiple_responsena_frequenciesnormality_testoneway_anovapairwise_wilcoxonpartial_corpearson_corphipompsread_porread_sasread_spssread_stataread_xlsxread_xptrecreliabilityrow_countrow_meansrow_sumsscheffe_testset_naspearman_rhostdstrip_tagst_testto_characterto_dummyto_labelto_labelledto_numerictukey_testunlabeluntag_naval_labelsvar_labelvar_label<-w_iqrw_kurtosisw_meanw_medianw_modusw_quantilew_rangew_sdw_sew_skeww_varwilcoxon_testwrite_spsswrite_statawrite_xlsxwrite_xpt

Dependencies:base64encclidigestdplyrfastmapgenericsgluehtmltoolslifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr

SPSS Compatibility Status
Summary | Tier Definitions | Per-Function Status | Active Exceptions | Validation Gaps | How to Read "SPSS-Compatible" | Methodology
Rendered fromspss-compatibility.Rmdusingknitr::rmarkdown

Last update: 2026-09-30
Started: 2026-05-19

Scale Analysis
Overview | Reliability Analysis | Basic Usage | Detailed Output | Interpreting Cronbach's Alpha | McDonald's Omega | With Survey Weights | Using tidyselect | Grouped Analysis | Exploratory Factor Analysis | Understanding the Output | Rotation Methods | Extraction Methods | Fixing the Number of Factors | Creating Scale Scores | Quick Scale Construction | Using the Scale in Analysis | Complete Example | Practical Tips | Summary | Next Steps
Rendered fromscale-analysis.Rmdusingknitr::rmarkdown

Last update: 2026-09-30
Started: 2026-03-01

Data Transformation
Overview | Recoding with rec() | Simple Recoding | Reverse-Coding | Dichotomizing | Keeping and Copying Values | Dummy Coding with to_dummy() | Basic Usage | Label-Based Column Names | Reference Category (n-1 Coding) | Adding to Existing Data | Standardization with std() | Basic Standardization | Standardization Methods | Weighted Standardization | Group-Wise Standardization | Centering with center() | Grand-Mean Centering | Group-Mean Centering | Weighted Centering | Row Operations | Row Means | Using tidyselect | Using pick() | Minimum Valid Items | Row Sums | Row Count | POMPS Transformation | Complete Example | Practical Tips | Summary | Next Steps
Rendered fromdata-transformation.Rmdusingknitr::rmarkdown

Last update: 2026-09-30
Started: 2026-03-14

Labels and Missing Values
Overview | Inspecting Labels | Variable Labels | Value Labels | Finding Variables | Setting Labels | Setting Variable Labels | Setting Value Labels | Converting Between Formats | Labelled → Factor | Labelled → Character | Factor → Numeric | Numeric/Factor → Labelled | Declaring Missing Values | Setting Values as Missing | Removing All Labels | Preserving Labels Through Pipelines | The Problem | The Solution: copy_labels() | Cleaning Unused Labels | Complete Example | Practical Tips | Summary | Next Steps
Rendered fromlabels-and-missing-values.Rmdusingknitr::rmarkdown

Last update: 2026-09-30
Started: 2026-03-14

Understanding Relationships: Correlation Analysis
Overview | Pearson Correlation | Basic Usage | With Survey Weights | Correlation Matrix | Detailed Output | Grouped Analysis | Spearman Correlation | Multiple Variables | Kendall's Tau | Partial Correlation | Interpreting Correlations | Strength Guidelines | Choosing the Right Method | Comparing Methods | Correlation Does Not Imply Causation | Complete Example | Reporting Results (APA Style) | Practical Tips | Summary | Next Steps
Rendered fromcorrelation-analysis.Rmdusingknitr::rmarkdown

Last update: 2026-09-29
Started: 2025-09-29

Descriptive Statistics and Frequencies
Overview | Summary Statistics with describe() | Basic Usage | Multiple Variables | With Survey Weights | Grouped Analysis | Choosing Statistics | Understanding the Output | Frequency Tables with frequency() | Basic Frequency | Weighted Frequencies | Grouped Frequencies | Cross-Tabulation with crosstab() | Basic Crosstab | Weighted Crosstabs | Grouped Crosstabs | Multiple Response Sets with multiple_response() | Data Dictionary with codebook() | Complete Example | Practical Tips | Summary | Next Steps
Rendered fromdescriptive-statistics.Rmdusingknitr::rmarkdown

Last update: 2026-09-29
Started: 2025-09-29

Introduction to mariposa
What is mariposa? | Key Features | The Example Dataset | Five-Minute Tour | 1. Explore the Data | 2. Transform Variables | 3. Compare Groups | 4. Post-Hoc Analysis | 5. Measure Relationships | 6. Build Models | Compact vs. Detailed Output | Grouped Analysis | Quick Reference | Data Import & Export | Label Management | Data Transformation | Descriptive Statistics | Hypothesis Testing | Post-Hoc & Effect Sizes | Scale Analysis | Regression | Weighted Statistics | Guides
Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2026-09-29
Started: 2025-06-30

Regression Analysis
Overview | Linear Regression | Simple Regression | Detailed Output | Understanding Coefficients | Multiple Regression | SPSS-Style Interface | With Survey Weights | Grouped Analysis | Interpreting R-squared | Using Transformed Predictors | Logistic Regression | When to Use | Basic Logistic Regression | Understanding Odds Ratios | Multiple Predictors | Interpreting Model Fit | Average Marginal Effects | Complete Example | Practical Tips | Summary | Next Steps
Rendered fromregression-analysis.Rmdusingknitr::rmarkdown

Last update: 2026-08-26
Started: 2026-03-01

Comparing Groups and Testing Hypotheses
Overview | Choosing the Right Test | Checking Normality First | t-Tests | Independent Samples | Multiple Variables at Once | One-Sample t-Test | Grouped Analysis | One-Way ANOVA | Post-Hoc Tests | Assumption Check | Factorial ANOVA | ANCOVA | Non-Parametric Tests | Mann-Whitney U Test | Kruskal-Wallis H Test | Wilcoxon Signed-Rank Test | Friedman Test | Binomial Test | Categorical Tests | Chi-Square Test of Independence | Effect Sizes for Categorical Data | Fisher's Exact Test | Chi-Square Goodness-of-Fit | McNemar's Test | Interpreting Results | p-Values | Effect Sizes | Multiple Comparisons | Complete Example | Practical Tips | Summary | Parametric Tests | Next Steps
Rendered fromhypothesis-testing.Rmdusingknitr::rmarkdown

Last update: 2026-08-26
Started: 2025-09-29

Importing and Exporting Data
Overview | Reading SPSS Files | Basic Import | Tagged Missing Values | Working with Tagged NAs | Reading Other Formats | Stata | SAS | SPSS Portable | Excel | Inspecting Imported Data | Exporting Data | Writing SPSS Files | Writing Stata Files | Writing SAS Transport Files | Writing Excel Files | Roundtripping: SPSS → R → SPSS | Practical Tips | Summary | Next Steps
Rendered fromdata-io.Rmdusingknitr::rmarkdown

Last update: 2026-07-02
Started: 2026-03-14

Working with Survey Weights
Overview | The Impact of Weights | Weighted Statistics Functions | Central Tendency | Dispersion | Distribution Shape | Precision and Range | Multiple Variables | Effective Sample Size | Weights in Analysis Functions | Grouped Weighted Analysis | Diagnosing Weight Issues | Checking Weight Distribution | Missing Weights | Weight Trimming | Complete Example | Best Practices | Summary | Next Steps
Rendered fromsurvey-weights.Rmdusingknitr::rmarkdown

Last update: 2026-03-14
Started: 2025-09-29

Readme and manuals

Help Manual

Help pageTopics
Analysis of Covariance: ANCOVAancova
ANOVA for a linear_regression modelanova.linear_regression
ANOVA for a logistic_regression modelanova.logistic_regression
Convert Analysis Results to Data Framesas.data.frame.ancova as.data.frame.binomial_test as.data.frame.chisq_gof as.data.frame.chi_square as.data.frame.codebook as.data.frame.crosstab as.data.frame.describe as.data.frame.dunn_test as.data.frame.efa as.data.frame.factorial_anova as.data.frame.fisher_test as.data.frame.frequency as.data.frame.friedman_test as.data.frame.kendall_tau as.data.frame.kruskal_wallis as.data.frame.levene_test as.data.frame.linear_regression as.data.frame.logistic_regression as.data.frame.mann_whitney as.data.frame.marginal_effects as.data.frame.mariposa as.data.frame.mcnemar_test as.data.frame.multiple_response as.data.frame.normality_test as.data.frame.oneway_anova as.data.frame.pairwise_wilcoxon as.data.frame.partial_cor as.data.frame.pearson_cor as.data.frame.reliability as.data.frame.scheffe_test as.data.frame.spearman_rho as.data.frame.tukey_test as.data.frame.t_test as.data.frame.wilcoxon_test as.data.frame.w_iqr as.data.frame.w_kurtosis as.data.frame.w_mean as.data.frame.w_median as.data.frame.w_modus as.data.frame.w_quantile as.data.frame.w_range as.data.frame.w_sd as.data.frame.w_se as.data.frame.w_skew as.data.frame.w_var
Test Whether a Proportion Matches an Expected Valuebinomial_test
Center Variables (Mean Centering)center
Test If Two Categories Are Relatedchi_square
Chi-Square Goodness-of-Fit Testchisq_gof
Create a Codebook for Your Datacodebook
Coefficients of a linear_regression modelcoef.linear_regression
Confidence intervals for linear_regression coefficientsconfint.linear_regression
Confidence intervals for logistic regression coefficientsconfint.logistic_regression
Copy Labels from One Data Frame to Anothercopy_labels
Compare Two Categories: See How They Relatecrosstab
Get to Know Your Numeric Datadescribe
Residual degrees of freedom of a linear_regression modeldf.residual.linear_regression
Remove Unused Value Labelsdrop_labels
Find Which Specific Groups Differ After Kruskal-Wallisdunn_test dunn_test.default
Explore the Structure Behind Your Survey Itemsefa
Compare Groups Across Multiple Factors: Factorial ANOVAfactorial_anova
Find Variables by Name or Labelfind_var
Fisher's Exact Test for Small Samplesfisher_test
Fitted values of a linear_regression modelfitted.linear_regression
Count How Many People Chose Each Optionfre frequency
Compare Three or More Related Measurements Without Assuming Normalityfriedman_test
Kendall's Tau Correlation Analysiskendall_tau
Compare Multiple Groups Without Assuming Normal Datakruskal_wallis
Test If Groups Vary Similarlylevene_test levene_test.ancova levene_test.data.frame levene_test.default levene_test.grouped_df levene_test.mann_whitney levene_test.oneway_anova levene_test.t_test
Run a Linear Regressionlinear_regression
Run a Logistic Regressionlogistic_regression
Standard glm accessors for logistic_regression resultscoef.logistic_regression fitted.logistic_regression logistic_regression-accessors nobs.logistic_regression residuals.logistic_regression vcov.logistic_regression
Longitudinal Study Data (Synthetic)longitudinal_data
Longitudinal Study Data - Wide Format (Synthetic)longitudinal_data_wide
Compare Two Groups Without Assuming Normal Datamann_whitney
Average Marginal Effectsmarginal_effects
McNemar's Test for Paired Proportionsmcnemar_test
Analyze Multiple Response Setsmultiple_response
Frequency Table of Missing Value Typesna_frequencies
Number of observations of a linear_regression modelnobs.linear_regression
Test Variables for Normalitynormality_test
Compare Multiple Groups: Are Their Averages Different?oneway_anova
Find Which Specific Measurements Differ After Friedman Testpairwise_wilcoxon pairwise_wilcoxon.default
Partial Correlationpartial_cor
Measure How Strongly Variables Are Relatedpearson_cor
Effect Sizes for Contingency Tablescramers_v goodman_gamma phi
Transform Scores to Percent of Maximum Possible (POMPS)pomps
Predict from a linear_regression modelpredict.linear_regression
Predict from a logistic_regression modelpredict.logistic_regression
Print ANCOVA results (compact)print.ancova
Print binomial test results (compact)print.binomial_test
Print chi-squared test results (compact)print.chi_square
Print chi-square goodness-of-fit test results (compact)print.chisq_gof
Print a Compact Console Overview of the Codebookprint.codebook
Print method for crosstab resultsprint.crosstab
Print method for describe objectsprint.describe
Print Dunn post-hoc test results (compact)print.dunn_test
Print EFA results (compact)print.efa
Print factorial ANOVA results (compact)print.factorial_anova
Print Fisher's exact test results (compact)print.fisher_test
Print method for frequency objectsprint.frequency
Print Friedman test results (compact)print.friedman_test
Print Kendall's tau results (compact)print.kendall_tau
Print Kruskal-Wallis test results (compact)print.kruskal_wallis
Print Levene test results (compact)print.levene_test
Print linear regression results (compact)print.linear_regression
Print logistic regression results (compact)print.logistic_regression
Print Mann-Whitney test results (compact)print.mann_whitney
Print average marginal effects (compact)print.marginal_effects
Print McNemar test results (compact)print.mcnemar_test
Print multiple response resultsprint.multiple_response
Print normality test results (compact)print.normality_test
Print ANOVA test results (compact)print.oneway_anova
Print pairwise Wilcoxon post-hoc test results (compact)print.pairwise_wilcoxon
Print partial correlation results (compact)print.partial_cor
Print Pearson correlation results (compact)print.pearson_cor
Print reliability results (compact)print.reliability
Print Scheffe test results (compact)print.scheffe_test
Print Spearman correlation results (compact)print.spearman_rho
Print summary of ANCOVA results (detailed output)print.summary.ancova
Print summary of binomial test results (detailed output)print.summary.binomial_test
Print summary of chi-squared test results (detailed output)print.summary.chi_square
Print summary of chi-square goodness-of-fit results (detailed output)print.summary.chisq_gof
Print a Detailed Console Codebook Summaryprint.summary.codebook
Print summary of crosstab results (detailed output)print.summary.crosstab
Print summary of describe results (detailed output)print.summary.describe
Print summary of Dunn post-hoc test results (detailed output)print.summary.dunn_test
Print summary of EFA results (detailed output)print.summary.efa
Print summary of factorial ANOVA results (detailed output)print.summary.factorial_anova
Print summary of Fisher's exact test results (detailed output)print.summary.fisher_test
Print summary of frequency results (detailed output)print.summary.frequency
Print summary of Friedman test results (detailed output)print.summary.friedman_test
Print summary of Kendall's tau correlation results (detailed output)print.summary.kendall_tau
Print summary of Kruskal-Wallis test results (detailed output)print.summary.kruskal_wallis
Print summary of Levene test results (detailed output)print.summary.levene_test
Print summary of linear regression results (detailed output)print.summary.linear_regression
Print summary of logistic regression results (detailed output)print.summary.logistic_regression
Print summary of Mann-Whitney test results (detailed output)print.summary.mann_whitney
Print summary of average marginal effects (detailed output)print.summary.marginal_effects
Print summary of McNemar test results (detailed output)print.summary.mcnemar_test
Print summary of multiple response results (detailed output)print.summary.multiple_response
Print summary of normality test results (detailed output)print.summary.normality_test
Print summary of one-way ANOVA results (detailed output)print.summary.oneway_anova
Print summary of pairwise Wilcoxon post-hoc test results (detailed output)print.summary.pairwise_wilcoxon
Print summary of partial correlation results (detailed output)print.summary.partial_cor
Print summary of Pearson correlation results (detailed output)print.summary.pearson_cor
Print summary of reliability analysis results (detailed output)print.summary.reliability
Print summary of Scheffe test results (detailed output)print.summary.scheffe_test
Print summary of Spearman correlation results (detailed output)print.summary.spearman_rho
Print summary of t-test results (detailed output)print.summary.t_test
Print summary of Tukey HSD test results (detailed output)print.summary.tukey_test
Print summary of w_quantile results (with Kish's effective N)print.summary.w_quantile
Print summary of a w_* statistic (detailed output)print.summary.w_statistic
Print summary of Wilcoxon signed-rank test results (detailed output)print.summary.wilcoxon_test
Print t-test results (compact)print.t_test
Print Tukey HSD test results (compact)print.tukey_test
Print method for w_modus objectsprint.w_modus
Print Wilcoxon signed-rank test results (compact)print.wilcoxon_test
Profile likelihood for a logistic_regression modelprofile.logistic_regression
Read SPSS Portable Data with Tagged Missing Valuesread_por
Read SAS Data with Tagged Missing Valuesread_sas
Read SPSS Data with Tagged Missing Valuesread_spss
Read Stata Data with Tagged Missing Valuesread_stata
Read Excel Data with Label Reconstructionread_xlsx
Read SAS Transport File with Tagged Missing Valuesread_xpt
Recode Variables Using String Syntaxrec
Check How Reliably Your Scale Measures a Conceptreliability
Residuals of a linear_regression modelresiduals.linear_regression
Count Occurrences of a Value Across Columnsrow_count
Compute Row Means Across Itemsrow_means
Compute Row Sums Across Itemsrow_sums
Compare All Groups More Conservatively After ANOVAscheffe_test scheffe_test.default
Declare Values as Missingset_na
Spearman's Rank Correlation Analysisspearman_rho
Standardize Variables (Z-Scores)std
Strip Tags from Tagged NAsstrip_tags
Summary method for ANCOVA resultssummary.ancova
Summary method for binomial test resultssummary.binomial_test
Summary method for chi-squared test resultssummary.chi_square
Summary method for chi-square goodness-of-fit test resultssummary.chisq_gof
Detailed Console Summary of the Codebooksummary.codebook
Summary method for crosstab resultssummary.crosstab
Summary method for describe resultssummary.describe
Summary method for Dunn post-hoc test resultssummary.dunn_test
Summarize an exploratory factor analysissummary.efa
Summary method for factorial ANOVA resultssummary.factorial_anova
Summary method for Fisher's exact test resultssummary.fisher_test
Summary method for frequency resultssummary.frequency
Summary method for Friedman test resultssummary.friedman_test
Summary method for Kendall's tau correlation resultssummary.kendall_tau
Summary method for Kruskal-Wallis test resultssummary.kruskal_wallis
Summary method for Levene test resultssummary.levene_test
Summary method for linear regression resultssummary.linear_regression
Summary method for logistic regression resultssummary.logistic_regression
Summary method for Mann-Whitney test resultssummary.mann_whitney
Summary method for average marginal effectssummary.marginal_effects
Summary method for McNemar test resultssummary.mcnemar_test
Summary method for multiple response resultssummary.multiple_response
Summary method for normality test resultssummary.normality_test
Summary method for one-way ANOVA resultssummary.oneway_anova
Summary method for pairwise Wilcoxon post-hoc test resultssummary.pairwise_wilcoxon
Summary method for partial correlation resultssummary.partial_cor
Summary method for Pearson correlation resultssummary.pearson_cor
Summarize a reliability analysissummary.reliability
Summary method for Scheffe test resultssummary.scheffe_test
Summary method for Spearman correlation resultssummary.spearman_rho
Summary method for t-test resultssummary.t_test
Summary method for Tukey HSD test resultssummary.tukey_test
Summary method for Wilcoxon signed-rank test resultssummary.wilcoxon_test
Social Survey Data (Synthetic)survey_data
Test If Two Groups Differt_test
Convert Labelled Variables to Characterto_character
Create Dummy Variables (One-Hot Encoding)to_dummy
Convert Labelled Variables to Factorsto_label
Convert Variables to Labelled Formatto_labelled
Convert Factors or Labelled Variables to Numericto_numeric
Find Which Specific Groups Differ After ANOVAtukey_test tukey_test.default
Remove All Label Metadataunlabel
Convert Tagged NAs Back to Original Codesuntag_na
Update and re-fit a linear_regression modelupdate.linear_regression
Update and re-fit a logistic_regression modelupdate.logistic_regression
Get or Set Value Labelsval_labels
Get or Set Variable Labelsvar_label var_label<-
Variance-covariance matrix of a linear_regression modelvcov.linear_regression
Measure Population-Representative Spread (IQR)w_iqr
Measure Population-Representative Kurtosisw_kurtosis
Calculate Population-Representative Averagesw_mean
Find the Population-Representative Middle Valuew_median
Find the Most Common Value in Your Populationw_modus
Calculate Population-Representative Percentilesw_quantile
Find the Range of Your Dataw_range
Calculate Population-Representative Standard Deviationsw_sd
Calculate Population-Representative Standard Errorsw_se
Measure Population-Representative Skewnessw_skew
Calculate Population-Representative Variancew_var
Compare Two Related Measurements Without Assuming Normalitywilcoxon_test
Export Data to SPSS Formatwrite_spss
Export Data to Stata Formatwrite_stata
Export Data to Excel with Label Supportwrite_xlsx write_xlsx.default write_xlsx.frequency
Export Data to SAS Transport Formatwrite_xpt