surveyframe 0.4.0

A major release. It adds multi-criteria decision analysis (10 methods), small-sample statistics, text and open-ended response analysis (9 methods), and a disclosed-amendment and Git-linked provenance trail for .sframe files, alongside 4 corrected results and 2 breaking changes. See below for full detail on each.

New: multi-criteria decision analysis (MCDA)

surveyframe’s decision-family extension links survey collection directly to 10 MCDA methods, closing the gap between MCDA computation packages, which assume a clean matrix already exists, and survey software, which has no concept of a decision method at all.

• 10 decision methods: the Analytic Hierarchy Process (AHP), the Analytic Network Process (ANP), the Decision Making Trial and Evaluation Laboratory method (DEMATEL), VIKOR, MOORA, SMART, WASPAS, PROMETHEE, ELECTRE, and TOPSIS. Every method carries a verified literature citation.
• 2 new item types collect judgement data directly inside the survey instrument: pairwise_comparison (Saaty’s 1-to-9 ratio scale for AHP and ANP, or a 0-to-4 directed influence scale for DEMATEL) and criteria_weight (a constant-sum allocation across criteria).
• A documented aggregation layer (R/decision_data.R) turns per-respondent answers into the matrices the methods consume: sframe_assemble_pairwise() builds one matrix per respondent and validates every pair was answered, sframe_aggregate_judgements() combines them (geometric mean for AHP/ANP, which preserves reciprocity, or arithmetic mean for DEMATEL), and sframe_rated_matrix() builds a performance matrix from ordinary matrix items. AHP judgements are additionally screened for consistency against Saaty’s random-index table, with the CR distribution reported whether or not a study has pre-declared a filtering threshold.
• Every ranking method resolves its matrix and weight inputs in the same order (a researcher-supplied override, then a collected item, then a typed error naming what is missing) and records where each input came from, so a results table states the provenance of every number.
• sensitivity_analysis() reports how far a ranking moves under a declared perturbation of the weights, and carries a degenerate flag so a ranking that never separated its alternatives cannot report false stability (see “Decision analysis: non-results now say so” below).
• Both the visual builder and SurveyStudio support the 2 new item types, and the static HTML survey, the Shiny module, and the builder preview render all 3 judgement-collection structures identically.
• RMCDA joins Suggests as a test-time cross-check oracle: an independent computation of the same method on the same matrix is required to agree with the package’s own result before a method’s implementation is accepted. This practice caught a real defect during development, a WASPAS runner that had inherited SMART’s normalisation step by mistake.

New: small-sample statistics

A track of corrections for comparisons run on small samples, where the ordinary versions of these tests can flip significance on repeated draws from data whose true difference never changed.

• The Hodges-Lehmann shift estimator as an alternative to the independent two-group Mann-Whitney comparison.
• The paired Wilcoxon pseudomedian confidence interval as an alternative to the paired t-test.
• The exact odds-ratio confidence interval on Fisher’s test for small 2x2 tables, avoiding the ad hoc continuity correction a conventional Wald interval needs when a cell is zero.
• Firth’s bias-reduced logistic regression (logistf in Suggests) for regression prone to separation at small n.
• A small-sample advisory surfaced on assumption_report() and sample_size_plan(), flagging when a study’s sample size falls in the range where these corrections are worth considering.
• vignettes/small-sample.Rmd walks through when to prefer each correction over its conventional counterpart.

New: text and open-ended response analysis

A 9-method text-analysis family for open-ended survey items, from term frequency through topic modelling, sharing the same analysis-plan, role-resolution, and reporting pipeline every other method family uses.

• term_freq: top terms by frequency, optionally split by a group variable, rendered as a bar chart or a word cloud.
• ngram_freq: top bigrams or trigrams by frequency.
• term_context: a keyword-in-context concordance table (before/match/ after) for a chosen keyword.
• co_occurrence: pairwise within-response co-occurrence counts on the top terms, rendered as a heatmap.
• co_occurrence_network: a Louvain-clustered (Blondel et al. 2008), force-directed (Fruchterman & Reingold 1991) term co-occurrence network; requires the optional igraph package.
• tidy_sentiment: positive/negative sentiment counts and proportion positive using the bing lexicon, optionally split by a group variable, rendered as a diverging bar chart or a positive/negative comparison word cloud; requires the optional tidytext package.
• quanteda_dfm: a document-feature matrix summary (feature count, sparsity, top features); requires the optional quanteda package.
• topic_model_lda: Latent Dirichlet Allocation topic modelling, top terms per topic as a ranked table and a faceted bar chart; requires the optional tidytext and topicmodels packages.
• stm_topics: structural topic modelling, the same top-terms-per-topic output; requires the optional stm and tidytext packages.
• A shared cleaning step (clean_text_responses()) and a 174-word Snowball-based English stopword list, both exported so a study can reuse or override them outside a runner.
• Both the visual builder and SurveyStudio support all 9 methods, including the word-cloud, top-N, seed, and topic-count (k) options that steer their plots and models.
• vignettes/text-analysis.Rmd walks through cleaning, each method, and what the family deliberately does not attempt (stemming/lemmatisation, tf-idf, and keyness comparison are not yet implemented).

New: disclosed amendments and a Git-linked provenance trail

write_sframe()’s SHA-256 hash proves a .sframe file is unchanged since it was written, but gives no way to distinguish a legitimate revision (a data-entry correction, bot-response removal, a documented model respecification) from an undisclosed edit – both break the hash identically. This release adds a disclosed-revision path alongside the existing hash check, without weakening it.

• amend_sframe() compares an instrument before and after a change and appends a structured, timestamped entry to an ordered amendment log – never overwrites – recording the reason (a controlled vocabulary: data_correction, bot_removal, model_respecification, instrument_revision, other), a free-text explanation, and which top-level fields changed.
• Two tiers, by default inferred from the reason: "pipeline" amendments (data corrections, bot removal) need only a reason. "design" amendments (anything touching the analysis plan or a model) require a deviation_report describing what changed in the research question, method, or model and why, matching how a formal preregistration deviation is normally handled. signoff is never left blank – it records a reviewer’s name or the literal "none", so an unreviewed design change stays visible to an auditor.
• amendment_log() returns the full history as a data frame, one row per disclosed amendment, exportable with write.csv().
• An edit made directly to a .sframe file, bypassing amend_sframe(), still fails read_sframe()’s integrity check exactly as before. The amendment log adds a disclosed path alongside the existing hash check.
• link_git_commit() records the current Git commit SHA and subject line alongside an instrument. This ties the SHA-256 hash to a specific, already-explained commit. It returns an informative message when Git isn’t installed or the path isn’t a repository. Git is optional.
• inst/schema/sframe_schema.json documents the .sframe format (every top-level field, including the new amendments log) as a standalone JSON Schema, so a reviewer or a second tool can read and validate a .sframe file without installing the package. .sframe was already plain, git-diffable JSON before this release; the schema makes that format explicit and independently checkable.
• vignettes/surveyframe.Rmd gains a “What the SHA-256 hash proves, and what it does not” section, stating plainly that the hash proves file identity, not methodological validity, and pointing to the design-time analysis_plan binding and run_analysis_plan()’s single-pass execution as the package’s separate, complementary defence against HARKing and p-hacking.

Corrected results (read before comparing against earlier output)

Four defects found by independent cross-validation are fixed. Each produced normal-looking numbers with no error or warning, so re-run any results computed with an earlier version.

• item_report() returned the wrong item-rest correlation. It subtracted each item from a rowMeans() total, which leaves roughly noise carrying the item negatively, so a highly reliable scale reported strong negative values. On simulated data with alpha 0.947 every item came back at about -0.46. The statistic is now the item against the sum of the other items in its scale, and matches psych::alpha()’s item.stats$r.drop to 1e-10.
• Repeated-measures ANOVA tested the condition effect against the wrong error term, because the subject identifier was left as an integer and aov() treated it as a continuous covariate. On a fixture where jmv::anovaRM() gives F(2, 78) = 86.93, surveyframe reported F = 1.45, p = 0.24. Correcting the identifier alone was not sufficient: the corrected design produces no Error: Within stratum, so the effect is now located by searching the strata directly.
• validate_sframe() rejected valid instruments. Its known-variable list held only base item and scale ids, so an analysis plan naming an expansion column (item__sub, item__option, item__a__vs__b, item__crit) failed validation for variables that do exist, including real exports from the visual builder. read_responses() already accepted those columns. Both now derive the list from one shared helper.
• The SEM syntax generators ignored the model type. seminr_syntax(), sem_lavaan_syntax(), and cfa_lavaan_syntax() never checked model$type, and the builder offered every saved model to all 3 generators, so a covariance-based model produced PLS-SEM syntax with no complaint. That is a runnable script estimating a model the researcher never declared. All 3 now refuse a mismatched estimation family, and the builder filters each model role to the types its generator can produce.

Breaking: validate_sframe() and validate_model() return a diagnostic

Both validators previously returned two different things depending on strict: the object itself, invisibly, when strict = TRUE, and a bare unclassed list when strict = FALSE. Neither was a diagnostic, the success path printed nothing at all, and the strict = FALSE return had no methods. Both now return an sframe_validation object, and they return it visibly, so validate_sframe(instrument) typed at the console shows the user what it found.

• The object records valid, every problems message, and a checks table listing all 18 instrument checks (10 for a model) whether or not each found anything. A diagnostic that lists only failures cannot tell a user that a check passed from one that was never reached.
• Read it with print(), summary() for the check roster, as.data.frame() for one row per problem, sf_is_valid(), and sf_problems().
• strict = TRUE still aborts with sframe_validation_error when anything is wrong. That has not changed.
• $valid and $problems keep working, so the common reading pattern needs no migration.
• What breaks: code using the strict = TRUE return as an instrument, as in instrument <- validate_sframe(instrument). Wrap it in as_sframe(). Passing a validation result where an instrument is expected now raises a directed error naming as_sframe() immediately.

Raised by a Journal of Statistical Software editor reviewing the code: “we would at least expect that the object is not silently returned and that the print method is adapted to allow the user to read directly the diagnostic”.

New: accessor and exploration methods for every class

The same review found that the classes carried print, summary and format only, so user code had no route to their contents except $ on the underlying list, which makes the internal layout part of the public contract. Two facts made that concrete: as.data.frame() failed on all 14 result classes with “cannot coerce class … to a data.frame”, and [ dropped the class on the list-backed reports, so results[1:2] silently degraded to a bare list and lost its print method.

• as.data.frame() now works on the instrument and on every report class, returning that object’s primary table.
• [ keeps the class on sframe_analysis_results, sframe_reliability_report and sframe_item_report.
• Instrument accessors: sf_meta(), sf_items(), sf_scales(), sf_choice_sets(), sf_branches(), sf_checks(), sf_models() and sf_plan(), with sf_plan<- for declaring the plan. The component accessors return an sf_component_list named by ID, so sf_items(instrument)[["sat_1"]] reaches one item.
• Component accessors: sf_id() and sf_label().
• Report accessors: sf_apa() and sf_flagged().
• Coercion: as_sframe().

The vignettes and the examples are rewritten to use these accessors. The registered S3 method count goes from 41 to 103.

Breaking: the Shiny collector now emits expansion columns

• render_survey() pipe-joined a matrix item’s cells into a single column, so a matrix question answered in the Shiny survey arrived as mx = "4|5" where read_responses() and the whole analysis layer expect mx__r1 and mx__r2. Data collected that way could not be read back by the package at all, and nothing said so at collection time. Ranking and multiple-choice items had the same shape problem.
• All 3 now emit the expansion columns that the static template and the Google Sheets collector already emitted: one column per matrix sub-item carrying its value, one per ranking option carrying its rank position, and one per multi-select option carrying 0 or 1.
• This changes the output shape of the Shiny collector. A study mid-collection through render_survey() will see its matrix, ranking, and multi-select columns change name and layout between versions. Responses already gathered under the old shape need re-shaping before they can be read, and the decision item types are unaffected because they emitted the correct columns from the start.

The rated performance matrix can now be wired in both GUIs

• SurveyStudio and the visual builder both offered an empty “Performance matrix items” dropdown for all 7 ranking methods (TOPSIS, VIKOR, MOORA, SMART, WASPAS, PROMETHEE, ELECTRE). That role matches on a "matrix" level, and neither surface gave matrix items one: the studio classified them as "identifier" and the builder grouped them under "expanded", which no role accepts. The effect was that the rated-matrix path, where respondents rate every alternative on every criterion, could only be built by writing R directly, even though it is one of the 3 declared ways to supply a decision matrix. Matrix items now carry their own "matrix" level in both surfaces.

Decision analysis: non-results now say so

• ELECTRE I reports when it establishes no outranking relation at all. On a 9-criterion problem at the default 0.70 and 0.30 thresholds no alternative clears concordance against any other, so every score is 0 and every alternative ranks 1. That is legitimate behaviour for the method, but the results table read as “all 9 alternatives are jointly best” and the APA sentence reported a kernel containing every alternative. A note now explains the equal ranks as an absence of evidence.
• sensitivity_analysis() gains a degenerate flag for the same reason. A ranking that never separated the alternatives cannot be changed by perturbing a weight, so every check passed and stable came back TRUE: the strongest robustness signal the function can give, produced by the weakest result it can be handed. print() now leads with “No result to test” instead of “Stable” in that case.

Data quality

• quality_report() counted only columns matching a bare item id, and multi-column items never post under those, so every expansion column was invisible to the missingness check. A respondent who skipped an entire pairwise battery was reported at 0 percent missing. Expansion columns now count as item data, which brings matrix, ranking, multi-select, and the 2 decision item types into the missingness figures for the first time. Reported missingness rates will change for any instrument using those item types, because columns that were silently excluded are now counted. Straight-lining and timing are unaffected: straight-lining runs over declared scales, and timing is measured on the clock.

Bundled demo data

• Both bundled demo instruments wired their seminr block to a cb_sem model, so sframe_demo_data() generated PLS-SEM syntax from a covariance-based model, and every vignette and example loading it inherited the same mismatch. Each demo now carries a real pls_sem model with composite constructs. The instrument hashes changed with it.

Decision analysis

• All 10 MCDM methods now return a citation. Previously only TOPSIS and AHP had one. Every reference was checked against the publication record.
• sframe_decision_options() documents PROMETHEE’s preference functions and records why the default is "usual", Brans and Vincke’s type I step function, chosen over the linear function several other implementations default to. Net flows differ between the 2 functions, and the ranking changed in 226 of 400 randomly drawn 4-alternative by 3-criterion matrices.

surveyframe 0.3.4

This release completes the plotting, interface, statistics, and reporting work started in 0.3.3. Every analysis family now has a chart, every effect size ships with a confidence interval, reports accept written interpretations and print to PDF, both dashboards gain quality and correlation panels, date questions gain bounds, and the builder and vignettes pass a WCAG 2.2 AA accessibility audit. Hard dependencies are unchanged. naniar and pagedown join Suggests.

Effect sizes and intervals

• Four new exported helpers, all base R: bootstrap_ci() (percentile bootstrap for any statistic), cohens_d_ci(), cramers_v_ci(), and eta_sq_ci().
• Analysis-plan runners attach a confidence interval to their effect size as a new result key: d_ci on the t-tests, r_ci on Mann-Whitney and Wilcoxon, eta_ci on ANOVA and Kruskal-Wallis, ci on the correlations (analytic Fisher z for Pearson, bootstrap for the rank methods), and v_ci on chi-square and cross-tabulation.
• APA strings and writing prompts now carry the interval, for example d = 0.62 [0.18, 1.05]. Data too small for an interval keeps the previous string.

Psychometrics

• validity_report() computes the Henseler heterotrait-monotrait ratio when item-level data is supplied through the new items_by_construct argument. Without it, the previous correlation-based fallback applies and the htmt_method element records which was used.
• missing_data_report() runs Little’s MCAR test when naniar is installed. Without naniar the result is unchanged.
• reliability_report() records why omega is unavailable for a scale in an omega_note, and the reliability chart names those scales in its subtitle.
• efa_solution() adds three tidy data frames ready for plotting and reporting: loadings_long, communalities_table, and variance_table.

Reports and codebook

• render_report(format = "pdf") prints the HTML report to PDF through pagedown, which requires a local Chrome or Chromium. HTML output is unchanged and remains the default.
• The report’s built-in styling now uses a small set of CSS variables, so a re-theme is a one-line change, and a print stylesheet paginates the report cleanly. Tables carry captions and header scopes, and every embedded chart has descriptive alternative text.
• The codebook now includes the pre-declared analysis plan and the saved measurement and structural models, so one document fully records the instrument a study used.
• The codebook’s items table shows each item’s actual response options and scale label directly, instead of an id that needed a separate choice-sets table to decode.
• Analysis-result tables (frequency, cross-tabulation, group comparisons, regression coefficients, and the rest) show item, scale, and response-option labels instead of the underlying ids and coded values.
• Report tables render as properly split HTML tables in both the Quarto and internal HTML report paths.

Written interpretations in reports

• New interpretations argument on render_report() and render_results(). Pass a named list keyed by analysis-plan block id to add a written interpretation to each research question after the results are known. The report shows it beside the pre-declared decision rule, so the prospective plan stays visible next to the post-hoc narrative. Interpretations are report content only and are never written into the instrument file.
• SurveyStudio’s Export screen gains an Interpretations card: one block per research question, in reading order (result table, chart, planned decision rule, then the interpretation), shown with the live result once responses are loaded. The generated report includes whatever you write there.
• A “Copy result” button on each Interpretations block copies the whole result, table, chart, and the interpretation as written, as one block, for pasting into a document.
• The SurveyBuilder Report outline now edits the planned decision rule inline, in sync with the research-question dialogue.

Charts

• run_analysis_plan(plots = TRUE) now attaches a chart to every supported family: regression diagnostics (4 panels), EFA scree and loadings heatmap, reliability bars, mosaic and crosstab, correlation heatmap, quality flag rates, group-comparison boxplots, paired slope charts, raw-variable distributions, repeated-measures profiles, a partial-correlation residual scatter, logistic-regression odds-ratio forest plots, a moderation interaction plot, and a mediation effect chart. Every analysis-plan block now returns a table, a chart, or generated syntax.
• Distribution shape by variable draws as a violin per variable, instead of a bar chart of the skewness and kurtosis summary statistics.
• A scale’s separate Likert items, and a matrix question’s rows, draw as one grouped diverging chart, instead of one chart per item.
• New plot() methods for descriptives, EFA, quality, reliability, validity, missing-data, and analysis-results objects. plot(results) draws every attached chart, and plot(results, which = "rq_id") returns one.
• New plot_palette argument on run_analysis_plan() and render_report(): "web" for brand colour on screen, "print" for black and white suitable for print and journal submission. SurveyStudio exposes the choice as a Chart theme option on the Export screen.
• SurveyStudio’s Analyse screen shows one result card per research question with its chart beneath the statistic.
• Both dashboards (the standalone response dashboard and the SurveyStudio Dashboard tab) gain a straight-lining flag-rate chart, a missing-data chart, and a scale-score correlation heatmap. All dashboard charts keep a base-graphics fallback, so ggplot2 remains optional.

Survey design

• Date questions accept date_min and date_max bounds in sf_item(), the SurveyBuilder, and the exported survey. The date picker enforces the bounds and typed dates outside them show a clear message.
• The SurveyBuilder ships a library of 14 preset choice sets, regenerates item ids safely when the response type changes, and expands matrix, ranking, and multiple-choice items into the same per-option variables that read_responses() produces.
• The survey thank-you page no longer forces a CSV download. It offers a “Download my response” button and honours a configured redirect.

Accessibility

• The SurveyBuilder interface passes an instrumented WCAG 2.2 AA audit with zero findings across its build, preview, and analyse screens and dialogues.
• All 7 vignettes pass the same audit: language metadata, AA contrast for links and code highlighting, wrapped code blocks, keyboard-reachable content, and alternative text on every chart.

Bug fixes

• sf_item()’s date_min and date_max accept only "YYYY-MM-DD" or a Date object now (an ambiguous string such as "01/02/2024" used to parse silently into a specific date depending on locale). Anything else raises a validation error.
• bootstrap_ci(), cohens_d_ci(), cramers_v_ci(), and eta_sq_ci() no longer alter the random-number seed for code that runs after a reproducible, seeded call.

surveyframe 0.3.3

This release adds an opt-in plotting layer, fixes bugs surfaced by the package’s first field deployment, and redesigns the survey-taking experience. ggplot2 joins Suggests; hard dependencies are unchanged.

Analysis and plotting

• New plots argument on run_analysis_plan() (default FALSE). When TRUE, supported analysis blocks return a ggplot object in $plot: bar charts for frequency and chi-square blocks, and scatter plots with a regression overlay for correlation and regression blocks.
• New exported theme_surveyframe(), a publication-oriented ggplot2 theme with an accessible fixed-order series palette. All plots use it.
• Inferential runners return a $table data frame ready for knitr::kable(); the HTML report shows these tables automatically.
• Frequency and cross-tab runners treat empty strings as missing values, so partially completed responses no longer form a blank category.
• Ranking items now export one column per option holding its rank (item__option = 1 for the top choice), so ranks are directly analysable. Multiple-choice items likewise export one 0/1 column per option instead of a single comma-joined column. read_responses() accepts the expanded columns for ranking, matrix, and multiple-choice items without warnings.
• render_report() now attaches each analysis block’s chart directly under its result table, in both the Quarto and internal HTML report paths, instead of tables and plots appearing in separate places.
• Likert items in the report’s response-distributions section get a diverging stacked bar chart (darkest at each pole, lightest next to neutral) instead of a plain frequency bar, so the direction and strength of opinion is visible at a glance.

Survey experience

• A full redesign of the exported survey: larger serif question typography, bordered option cards with selection ticks, numbered Likert squares, restyled matrix, slider, and ranking blocks, and a slim top progress bar. Every colour derives from the instrument’s single theme colour, so one colour choice re-skins the whole survey. Touch targets meet a 44 pixel minimum on phones.
• Branching rules on one question now combine with AND, and hiding a controlling question also hides everything that depends on it, so screening logic behaves as declared even when answers change.
• Single-page surveys show answered-questions progress (for example “12 of 44 answered”); numeric questions respect declared minimum and maximum bounds.
• Branching rules can now show and hide section breaks and text blocks, so a branched text block works as a screen-out message (“Sorry, you are not eligible”) and section headings disappear with their questions.
• A matrix question reflows into stacked, labelled row-cards below 600 pixels instead of a table that needs horizontal scrolling to complete.
• The exported survey meets WCAG 2.2 AA on an instrumented audit: every input carries an accessible name, keyboard focus is visible on option cards, errors are announced to assistive technology, required questions are marked beyond colour, ranking items gain keyboard reorder buttons, headings are real headings, and all touch targets and text contrast meet the standard.

Data collection

• Fixed a bug that silently blocked submissions from hosted surveys: the Google Apps Script POST now avoids the CORS preflight that Apps Script never answers. Collectors no longer emit columns for section breaks or text blocks.
• read_sheet_responses() gains a meta_cols argument for extra sheet columns a host application appends, and SurveyStudio’s dashboard now computes completion times from imported sheet responses.

Model syntax

• sem_lavaan_syntax() turns free-text path labels into valid lavaan parameter names (a label starting “H1:” becomes the parameter H1).
• seminr_syntax() output loads seminr and uses summary() accessors, so the generated code runs as pasted.
• run_analysis_plan() accepts pls_sem as an alias for seminr_syntax.

SurveyBuilder and report

• Opening a .sframe verifies and reports its SHA-256 integrity status.
• New choice questions start with a fresh option set, and editing shared options forks the set first, so options never leak between questions.
• The analysis-plan modal blocks using one variable in two roles, and the test suggester handles Likert items and multi-group comparisons sensibly.
• Reports print generated model syntax in code blocks and show reliability results as a table.
• “+ Add question” now opens the question-type picker instead of silently adding a Likert item, and the redundant icon-only button next to it is gone. Survey settings live only in the sidebar; the top bar no longer duplicates that entry point.

surveyframe 0.3.2

This release corrects the package citation, completes the S3 method surface for the component classes, and improves the graphical tools and the HTML report. It adds no new exported functions, no new statistical methods, and no new bundled datasets.

Citation and methods

• inst/CITATION now reports the correct package title and reads the version dynamically from the package metadata, so the citation no longer pins an old version or an outdated title.
• Added print(), format(), and summary() methods for the component classes sf_choices, sf_item, sf_scale, sf_branch, sf_check, and sf_model, so each class now has a visible, documented S3 surface.
• lavaan is declared in Suggests. It is used only to fit the syntax produced by cfa_syntax(). The package itself generates syntax and never requires lavaan to be installed.

Graphical tools

• SurveyBuilder exports a deployable survey in the browser through a new Export survey button, and generates the Google Sheets Apps Script collector through a Generate collector button. Both reuse the same templates the R functions use, so the output matches export_static_survey() and export_google_sheet().
• The builder Analyse tab shows three distinct stages: Plan, Run preview (the methods that need response data), and Report outline (analyses plus measurement models). Analysis plans can be reordered by dragging.
• The exported survey carries a “Built with surveyframe” footer, sizes a header logo consistently across aspect ratios, shows a page progress indicator only on multi-page surveys, and gains a mobile layout.
• SurveyStudio opens an instrument designed in the builder, previews the exact deployable survey in a frame, and analyses uploaded responses. The response dashboard, with an overview, item and scale distributions, and a raw-data table, is now built into the studio. A button loads the bundled sample survey and 120 responses. Survey design moved entirely to the builder.

HTML report

• render_report() renders reliably through Quarto when it is installed. A path defect that made the Quarto render fail and fall back to the plain internal output is fixed.
• Reports include a response distributions section, with one chart per item and one per scale, in both the Quarto output and the built-in HTML fallback.
• Tables are formatted, wide tables scroll within the page, the table of contents sits on the left, and numeric values are rounded to two decimal places.

Documentation

• Added the “Deploying a survey and collecting responses on free hosting” vignette, covering the Apps Script collector, GitHub Pages and Blogger hosting, and reading the responses back into R.

surveyframe 0.3.1

This is a patch release. It fixes the static-survey to Google Sheets to R collection loop, repairs a serialisation defect, and improves the first-time user experience. There are no new exported functions, no new statistical methods, and no new bundled datasets.

Bug fixes

Data collection round-trip

• export_static_survey() now renders the header logo and institution name from render$header, so exported surveys match the Shiny renderer and the builder preview.
• export_static_survey() now falls back to the instrument’s render$google_sheets_endpoint when endpoint_url is not supplied, so a Google Sheets endpoint set in the builder is honoured on export.
• The static survey now posts the respondent identifier under the column name respondent_id, matching the Google Apps Script collector and read_responses(). The collection round-trip now preserves the identifier.
• export_google_sheet() now includes matrix sub-item columns (item_id__sub) in the Apps Script header row, so matrix answers are stored in the Sheet.
• read_sheet_responses() now declares started_at as a meta column and no longer raises a warning on every read.
• Survey logos now keep their original MIME type (image/png, image/jpeg, image/gif), so JPEG and GIF logos display correctly in the builder, the Shiny renderer, and the static export.

Serialisation

• write_sframe() now strips list-level names from the item, choice, scale, branching, check, and model collections before serialisation. Instruments built with Map() or other helpers that attach element names (for example, using item IDs as names) previously serialised those collections as keyed JSON objects, producing a hash mismatch and an integrity error on read_sframe(). Saved instruments now round-trip correctly regardless of how the component lists were constructed.

User experience

• Every exported function that takes an instrument now reports a clear, actionable message when passed something that is not an sframe object. The message points the user to sf_instrument() and read_sframe() instead of showing a raw inherits() assertion failure.
• reliability_report() no longer prints psych internal warnings to the console. McDonald’s omega is skipped silently for scales with fewer than three items, where the statistic is not meaningful.
• The error message from run_analysis_plan() when no analysis plan is present now describes both the programmatic route (instrument$analysis_plan) and the visual SurveyBuilder route.

Documentation

• Rewrote the main vignette (surveyframe.Rmd) as an end-to-end worked example: design the questionnaire, export it as a hosted survey with a Google Sheets backend, collect responses, score them, run the analysis plan, and render a report. The results section uses simulated responses so the vignette builds offline; a single read_sheet_responses() call connects the same workflow to live responses. The questionnaire and concept are adopted from Sharafuddin, Madhavan, and Wangtueai (2024, Administrative Sciences, 14(11), 273, doi:10.3390/admsci14110273), with generic destination wording so the example transfers to any tourism services context.
• Updated the supporting vignettes to reflect the research-design-first workflow where the instrument holds the questions, the analysis plan, and the measurement model.
• sf_instrument() examples now include a complete analysis_plan block.
• The README now leads with install.packages("surveyframe"), adds a short path for users who already have a response CSV, and points to browseVignettes("surveyframe").

surveyframe 0.3.0

The first CRAN release of the full workflow: a typed instrument object carrying the questions, the analysis plan, and the measurement model, with deployment, collection, analysis, and reporting built around it.

New features

Analysis planning, survey statistics, and model syntax

• Added a role-based analysis-plan structure while preserving old variables/test analysis blocks. New plans can store family, method, roles, options, hypotheses, decision_rule, reporting_references, status, and requires_data.
• Added common survey analysis helpers: descriptives_report(), missing_data_report(), assumption_report(), posthoc_report(), validity_report(), and sample_size_plan().
• Expanded run_analysis_plan() to dispatch the v0.3 method registry, including descriptives, missing data, sparse-table tests, related-sample tests, Kendall and partial correlations, two-way ANOVA, ANCOVA, repeated ANOVA, ordinal and multinomial logistic regression, mediation, moderation, and model-syntax output.
• Added a model specification layer: sf_construct(), sf_path(), sf_covariance(), sf_indirect(), sf_model(), validate_model(), model_json(), add_model(), efa_solution(), efa_syntax(), cfa_lavaan_syntax(), sem_lavaan_syntax(), seminr_syntax(), and model_report_template(). Syntax generation does not require lavaan or seminr.
• cfa_syntax() remains available as a backward-compatible wrapper around cfa_lavaan_syntax().
• SurveyBuilder Analyse mode now uses a three-panel Plan/Run/Report workspace with variable metadata badges, role-based variable assignment, method options, output preview, reporting references, and a table-based model builder. Significance level is shown only for inferential methods.

Static HTML survey export

• Added export_static_survey(). This produces a single, self-contained HTML file that runs the survey in any modern browser without a Shiny server or an internet connection. All thirteen item types are fully rendered (Likert, single choice, multiple choice, matrix, numeric, text, long text, date, slider, rating, ranking, section break, text block). Branching logic, required-field validation, a progress bar, welcome and thank-you pages are all handled in client-side JavaScript. On submission the browser downloads a per-respondent CSV file. An optional endpoint_url argument adds a parallel JSON POST to any serverless endpoint (Google Apps Script, Netlify function, etc.).

  The exported file is suitable for hosting on GitHub Pages, Netlify, or any static file server, and can also be shared directly as an e-mail attachment and opened from disk.

  The SHA-256 hash written into .sframe files by write_sframe() and by the SurveyBuilder HTML is computed using the same canonicalisation algorithm, so instruments round-trip correctly between the browser and R.

Interactive response dashboard

• Added launch_dashboard(). Opens a five-panel Shiny dashboard for exploring collected response data alongside the instrument definition, without modifying either. The panels are: Overview (response count, date range, instrument metadata), Items (per-item bar charts, histograms, and frequency tables), Scales (scale score distributions with mean overlay), Quality (attention-check pass rates), and Raw data (a scrollable response table with CSV download).

  When called without arguments the dashboard loads the bundled tourism services demo. When called with a user-supplied instrument and no responses argument, it opens in metadata-only mode showing instrument structure.

• Added sframe_demo_data(), sframe_input_types_demo_data(), launch_builder_demo(), launch_studio_demo(), and launch_dashboard_demo() for CRAN-safe examples, training, and local GUI testing.

• Added a bundled input-types demo instrument and simulated response dataset for testing SurveyBuilder, SurveyStudio, the dashboard, and all supported item controls.

• launch_studio() now accepts preloaded instruments, response data frames, CSV response paths, initial screen selection, host, port, and browser control. SurveyStudio reads these preloaded values during startup.

Shiny survey module

• Added survey_module_ui() and survey_module_server(). These allow a survey to be embedded inside a larger Shiny application as a first-class module. survey_module_server() returns a reactive that holds NULL until the form is submitted, then returns the response as a named list keyed by item ID.

  ui <- fluidPage(survey_module_ui("s1"))
  server <- function(input, output, session) {
    resp <- survey_module_server("s1", instrument = instr)
    observeEvent(resp(), { saveRDS(resp(), "response.rds") })
  }

  An optional on_submit callback fires immediately on submission, before any observeEvent() elsewhere in the app.

Extended analysis plan tests

run_analysis_plan() now implements four additional tests used by the SurveyBuilder’s test dropdown:

• anova_one: One-way ANOVA with eta-squared effect size. When the result is significant and there are more than two groups, Tukey HSD post-hoc output is included in the result object.
• t_test_pair: Paired-samples t-test with Cohen’s d_z.
• wilcoxon_pair: Wilcoxon signed-rank test with r effect size.
• regression_logistic_binary: Binary logistic regression with McFadden R-squared and an overall model chi-square test. The full coefficient table is returned for interpretation.

All four runners produce an APA-formatted summary string and an interpretation prompt field to guide write-up.

Bug fixes

• write_sframe() validates the instrument and writes the validated object, preserving meta$validated = TRUE in the saved .sframe file.

• .sframe serialisation now includes a models field and continues to read older .sframe files where models is absent.

• read_responses() no longer requires display-only items such as section_break and text_block to appear as response columns.

• validate_sframe() now checks model references, analysis-plan roles, invalid model IDs, duplicate model IDs, and model indicator/path integrity.

• launch_builder(open = TRUE) opens the SurveyBuilder HTML in the system’s default browser via utils::browseURL().

• R/studio_builder.R contains three fully implemented internal functions (sframe_builder_empty_state, sframe_builder_state_from_instrument, sframe_builder_validate_draft) used by SurveyStudio startup and draft validation.

• SHA-256 hashing in the SurveyBuilder HTML includes a pure-JavaScript fallback for environments where crypto.subtle is unavailable on file:// origins, including common Firefox file:// configurations. Saving a .sframe file from the builder now always succeeds.

• The SurveyBuilder’s rqSuggest box now appears with an icon and a plain-language recommendation when two or more variables are selected in the RQ modal.

• The undo and redo buttons in the SurveyBuilder topbar are now correctly disabled when their respective history stacks are empty.

Security hardening

• export_google_sheet() now writes Google Apps Script using JSON-encoded JavaScript literals instead of interpolating instrument metadata directly into executable code. The generated endpoint also rejects missing, over-large, and non-object JSON POST bodies.
• SurveyStudio upload handlers now validate uploaded .sframe and .csv files by extension, size, and text-content checks before passing them to import functions.
• read_sframe() now validates the top-level .sframe payload structure before hash verification and object reconstruction.
• Internal HTML report generation now applies escaping consistently to report titles, instrument metadata, citations, and effect labels.
• Quarto report rendering now cleans temporary render directories and RDS files with on.exit() even when rendering fails.

Documentation

• validate_sframe(), score_scales(), codebook_report(), cfa_syntax(), and launch_builder(open = FALSE) have fully runnable examples.
• Reworked the vignette set into a coherent workflow covering instrument building, response analysis, reliability and validity, EFA/CFA/SEM/PLS syntax generation, and GUI usage.
• The demo launchers (launch_builder_demo(), launch_studio_demo(), and launch_dashboard_demo()) open in the browser with the demo instrument, scales, and analysis plan preloaded, so no manual file loading is needed.
• The interactive package demo (demo("survey")) walks through the whole workflow with step-by-step prompts.

Dashboard and report polish

• The dashboard parses response dates in the common formats (ISO 8601, date-only, UK and US day orders) instead of erroring on non-standard strings, colour-codes quality rows by flag status, matches the download button to the active theme, and draws the Items and Scales charts as soon as their tabs open.
• HTML report tables use APA formatting, with horizontal rules only and a significance footnote added automatically when a p-value column is present.

surveyframe 0.1.0

• Initial release.
• Core S3 object system: sf_instrument(), sf_item(), sf_choices(), sf_scale().
• Serialisation: write_sframe(), read_sframe() with SHA-256 integrity checking.
• Shiny survey renderer: render_survey().
• Static SurveyBuilder HTML: launch_builder().
• Response reader: read_responses().

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