AiSEM 0.7.0-alpha.1

AiSEM 0.7: AI Native Structural Equation Modeling Software, free CB-SEM and PLS-SEM written from scratch and backed by published research. Free to download and use, including for business (see LICENSE). AiSEM was called OpenSEM up to version 0.6.

The AiSEM app. Double-click aisem (or run aisem) and the app opens in your web browser. Everything runs on your own computer; only what you choose to share goes to the AI provider you pick.

New in 0.7: AI Copilot

• Autopilot runs the whole study: it reads your column summaries, drafts the model, chooses the methods, runs the analysis, reviews the results against published guidelines, improves the model and writes up the findings, with a full activity log
• Full Auto, or Ask Before Each Change; choose which steps the AI does and how many review rounds
• AiSEM checks every AI suggestion before use: models are parsed and matched to your columns (the AI repairs rejected models), settings are checked against the allowed choices
• Number verification: every number in an AI write-up or answer is matched against the computed report, and any number not found is flagged
• AI buttons on each step: Draft with AI, Recommend Settings with AI, AI Review, AI Write-Up, plus Ask the AI about your data and results
• Providers: OpenAI (ChatGPT), Anthropic (Claude), Google Gemini, DeepSeek, Moonshot (Kimi), Z.ai and Zhipu (GLM), xAI (Grok), Meta (Muse), Alibaba Cloud Model Studio (Qwen), Mistral, Groq, OpenRouter, any OpenAI-compatible service, and free private models on your own computer with Ollama or LM Studio
• Free options: Gemini, GLM Flash, Mistral and Groq free tiers, OpenRouter free models, and local models
• The model list is loaded live from each provider, so new models appear without an update
• Privacy: choose Column Names Only, Column Summaries (default) or Summaries and First 15 Rows; keys stay on this computer, are masked on screen, never appear in reports or project files, and are saved (owner-only file) only if you tick Remember on This Computer

New in 0.7: Advanced Models

• Bayesian SEM: Gibbs sampler with 4 chains on all CPU cores; posterior means, medians, credible intervals, one-tailed p, standardized estimates, indirect effects, R-squared, rank-normalized R-hat and effective sample size, posterior predictive p value and DIC (--estimator bayes)
• Two-level SEM for clustered data: intraclass correlations, design effects, and the model fitted within and between clusters (--cluster <column>)
• Latent class and latent profile analysis (categorical, continuous or mixed items, missing values allowed): 1 to K classes with AIC, BIC, sample-size adjusted BIC, CAIC, entropy, bootstrap likelihood ratio test, class sizes, average posterior probabilities and item profiles (--classes <K>)
• FIMIX-PLS hidden segments in every PLS-SEM run: AIC, AIC3, AIC4, BIC, CAIC, HQ, MDL5, EN and NEC for 1 to 4 segments, a suggested segment count, and segment-specific paths and R-squared (--segments <K>)
• Necessary condition analysis in every PLS-SEM run: CE-FDH and CR-FDH ceilings, effect size d, permutation test, accuracy, inefficiencies and bottleneck tables (--nca-perms <N>)
• Rename: the program is now aisem (was opensem); OpenSEM project files and saved work still open

New in 0.6: Ordinal Data

• WLSMV for Likert-type and other ordered-category items: thresholds, polychoric correlations with their asymptotic covariance matrix, diagonally weighted least squares, robust standard errors and the mean-and-variance adjusted chi-square, with CFI, TLI and RMSEA from the adjusted statistics
• Auto Mode picks WLSMV when every item has 2 to 4 categories and no values are missing; choose it yourself with --estimator wlsmv or Ordinal Items (WLSMV) in the app
• Polychoric correlations run on every CPU core

New in 0.5

• More CB-SEM estimators: generalized least squares (GLS), unweighted least squares (ULS) and asymptotically distribution-free (ADF / WLS), in the app and with --estimator gls|uls|adf
• Monte Carlo power analysis for every structural path at your sample size, and the sample size that gives every path 80% power
• Fix: no crash when an estimator has no chi-square test (ULS)

New in 0.4: The AiSEM App

• Four guided steps: Data, Model, Run, Results
• Load a CSV or TSV file by drag and drop, with a preview and missing-value count, or try the demo data
• Visual path diagram editor: add constructs, tick their items, connect paths by clicking, drag to arrange, reflective or formative; loops are refused
• Suggest Model groups items by name (T1, T2, T3 become construct T); Tidy Layout arranges the diagram
• Model text stays in sync with the diagram and can be edited directly
• Run with Auto Mode or choose method, estimator, resamples, confidence level, seed, group comparison and IPMA scale
• The full report opens in the app; Save Report keeps it as an HTML file
• Save Project and Open Project keep data, model and settings in one file
• Security: the app listens only on this computer, needs a secret per-session link, rejects other websites and uses a strict content security policy

New in 0.3: PLS-SEM Add-Ons

• PLSpredict: 10-fold cross-validation repeated 10 times, RMSE and MAE against a linear-model benchmark, Q2_predict, and the predictive-power verdict
• Multigroup analysis with --group <column>: permutation test of path differences (PLS-MGA) for every pair of groups
• MICOM measurement invariance: compositional invariance, equal means and equal variances
• Importance-performance map analysis (IPMA) for each final outcome construct

New in 0.2: CB-SEM

• Maximum likelihood estimation (Fisher scoring) with standard errors and the completely standardized solution
• Robust ML (Satorra-Bentler scaled chi-square and robust standard errors) for non-normal data
• FIML for missing data, compared against the EM saturated model
• Chi-square, CFI, TLI, RMSEA with 90% confidence interval and test of close fit, SRMR, AIC, BIC
• Modification indices with expected parameter change
• Bollen-Stine bootstrap model test and Mardia normality tests
• Residual covariances in the model syntax: x1 ~~ x2

New in 0.2: Mediation

• Specific and total indirect effects for CB-SEM and PLS-SEM, with bootstrap intervals (delta method under FIML)
• Mediation type for each indirect effect (complementary, competitive, indirect-only, direct-only, no effect)

Auto Mode

• Chooses CB-SEM for reflective models and PLS-SEM when a construct is formative
• Chooses ML, robust ML or FIML from the data, and falls back to PLS-SEM with an explanation if CB-SEM cannot be estimated

Still Included

• PLS path modelling and consistent PLS, reliability, AVE, HTMT, VIF, f squared, bootstrap on all CPU cores
• Self-contained HTML report with APA-style tables, a methods paragraph and the full reference list

Quick Start

1. Download the file for your system below and unzip it.
2. Double-click aisem (Windows: aisem.exe). The app opens in your browser; keep the small window open while you work.
3. Command line also works: aisem analyze --data mydata.csv --model mymodel.txt

Run aisem --help for the model syntax and all options. Each download has a .sha256 checksum. The macOS build is not notarised yet; if macOS blocks it, right-click the file and choose Open.

OpenSEM 0.6.0-alpha.1

OpenSEM 0.6: free CB-SEM and PLS-SEM software, written from scratch and backed by published research. Free to download and use, including for business (see LICENSE).

New: the OpenSEM app. Double-click opensem (or run opensem) and the app opens in your web browser. Everything runs on your own computer; nothing is uploaded.

New in 0.6: Ordinal Data

• WLSMV for Likert-type and other ordered-category items: thresholds, polychoric correlations with their asymptotic covariance matrix, diagonally weighted least squares, robust standard errors and the mean-and-variance adjusted chi-square, with CFI, TLI and RMSEA from the adjusted statistics
• Auto Mode picks WLSMV when every item has 2 to 4 categories and no values are missing; choose it yourself with --estimator wlsmv or Ordinal Items (WLSMV) in the app
• Polychoric correlations run on every CPU core

New in 0.5

• More CB-SEM estimators: generalized least squares (GLS), unweighted least squares (ULS) and asymptotically distribution-free (ADF / WLS), in the app and with --estimator gls|uls|adf
• Monte Carlo power analysis for every structural path at your sample size, and the sample size that gives every path 80% power
• Fix: no crash when an estimator has no chi-square test (ULS)

New in 0.4: The OpenSEM App

• Four guided steps: Data, Model, Run, Results
• Load a CSV or TSV file by drag and drop, with a preview and missing-value count, or try the demo data
• Visual path diagram editor: add constructs, tick their items, connect paths by clicking, drag to arrange, reflective or formative; loops are refused
• Suggest Model groups items by name (T1, T2, T3 become construct T); Tidy Layout arranges the diagram
• Model text stays in sync with the diagram and can be edited directly
• Run with Auto Mode or choose method, estimator, resamples, confidence level, seed, group comparison and IPMA scale
• The full report opens in the app; Save Report keeps it as an HTML file
• Save Project and Open Project keep data, model and settings in one file
• Security: the app listens only on this computer, needs a secret per-session link, rejects other websites and uses a strict content security policy

New in 0.3: PLS-SEM Add-Ons

• PLSpredict: 10-fold cross-validation repeated 10 times, RMSE and MAE against a linear-model benchmark, Q2_predict, and the predictive-power verdict
• Multigroup analysis with --group <column>: permutation test of path differences (PLS-MGA) for every pair of groups
• MICOM measurement invariance: compositional invariance, equal means and equal variances
• Importance-performance map analysis (IPMA) for each final outcome construct

New in 0.2: CB-SEM

• Maximum likelihood estimation (Fisher scoring) with standard errors and the completely standardized solution
• Robust ML (Satorra-Bentler scaled chi-square and robust standard errors) for non-normal data
• FIML for missing data, compared against the EM saturated model
• Chi-square, CFI, TLI, RMSEA with 90% confidence interval and test of close fit, SRMR, AIC, BIC
• Modification indices with expected parameter change
• Bollen-Stine bootstrap model test and Mardia normality tests
• Residual covariances in the model syntax: x1 ~~ x2

New in 0.2: Mediation

• Specific and total indirect effects for CB-SEM and PLS-SEM, with bootstrap intervals (delta method under FIML)
• Mediation type for each indirect effect (complementary, competitive, indirect-only, direct-only, no effect)

Auto Mode

• Chooses CB-SEM for reflective models and PLS-SEM when a construct is formative
• Chooses ML, robust ML or FIML from the data, and falls back to PLS-SEM with an explanation if CB-SEM cannot be estimated

Still Included

• PLS path modelling and consistent PLS, reliability, AVE, HTMT, VIF, f squared, bootstrap on all CPU cores
• Self-contained HTML report with APA-style tables, a methods paragraph and the full reference list

Quick Start

1. Download the file for your system below and unzip it.
2. Double-click opensem (Windows: opensem.exe). The app opens in your browser; keep the small window open while you work.
3. Command line also works: opensem analyze --data mydata.csv --model mymodel.txt

Run opensem --help for the model syntax and all options. Each download has a .sha256 checksum. The macOS build is not notarised yet; if macOS blocks it, right-click the file and choose Open.

OpenSEM v0.5.0-alpha.1

OpenSEM 0.5: free CB-SEM and PLS-SEM software, written from scratch and backed by published research. Free to download and use, including for business (see LICENSE).

New: the OpenSEM app. Double-click opensem (or run opensem) and the app opens in your web browser. Everything runs on your own computer; nothing is uploaded.

New in 0.5

• More CB-SEM estimators: generalized least squares (GLS), unweighted least squares (ULS) and asymptotically distribution-free (ADF / WLS), in the app and with --estimator gls|uls|adf
• Monte Carlo power analysis for every structural path at your sample size, and the sample size that gives every path 80% power
• Fix: no crash when an estimator has no chi-square test (ULS)

New in 0.4: The OpenSEM App

• Four guided steps: Data, Model, Run, Results
• Load a CSV or TSV file by drag and drop, with a preview and missing-value count, or try the demo data
• Visual path diagram editor: add constructs, tick their items, connect paths by clicking, drag to arrange, reflective or formative; loops are refused
• Suggest Model groups items by name (T1, T2, T3 become construct T); Tidy Layout arranges the diagram
• Model text stays in sync with the diagram and can be edited directly
• Run with Auto Mode or choose method, estimator, resamples, confidence level, seed, group comparison and IPMA scale
• The full report opens in the app; Save Report keeps it as an HTML file
• Save Project and Open Project keep data, model and settings in one file
• Security: the app listens only on this computer, needs a secret per-session link, rejects other websites and uses a strict content security policy

New in 0.3: PLS-SEM Add-Ons

• PLSpredict: 10-fold cross-validation repeated 10 times, RMSE and MAE against a linear-model benchmark, Q2_predict, and the predictive-power verdict
• Multigroup analysis with --group <column>: permutation test of path differences (PLS-MGA) for every pair of groups
• MICOM measurement invariance: compositional invariance, equal means and equal variances
• Importance-performance map analysis (IPMA) for each final outcome construct

New in 0.2: CB-SEM

• Maximum likelihood estimation (Fisher scoring) with standard errors and the completely standardized solution
• Robust ML (Satorra-Bentler scaled chi-square and robust standard errors) for non-normal data
• FIML for missing data, compared against the EM saturated model
• Chi-square, CFI, TLI, RMSEA with 90% confidence interval and test of close fit, SRMR, AIC, BIC
• Modification indices with expected parameter change
• Bollen-Stine bootstrap model test and Mardia normality tests
• Residual covariances in the model syntax: x1 ~~ x2

New in 0.2: Mediation

• Specific and total indirect effects for CB-SEM and PLS-SEM, with bootstrap intervals (delta method under FIML)
• Mediation type for each indirect effect (complementary, competitive, indirect-only, direct-only, no effect)

Auto Mode

• Chooses CB-SEM for reflective models and PLS-SEM when a construct is formative
• Chooses ML, robust ML or FIML from the data, and falls back to PLS-SEM with an explanation if CB-SEM cannot be estimated

Still Included

• PLS path modelling and consistent PLS, reliability, AVE, HTMT, VIF, f squared, bootstrap on all CPU cores
• Self-contained HTML report with APA-style tables, a methods paragraph and the full reference list

Quick Start

1. Download the file for your system below and unzip it.
2. Double-click opensem (Windows: opensem.exe). The app opens in your browser; keep the small window open while you work.
3. Command line also works: opensem analyze --data mydata.csv --model mymodel.txt

Run opensem --help for the model syntax and all options. Each download has a .sha256 checksum. The macOS build is not notarised yet; if macOS blocks it, right-click the file and choose Open.

OpenSEM v0.4.0-alpha.1: The OpenSEM App

OpenSEM 0.4: free CB-SEM and PLS-SEM software, written from scratch and backed by published research. Free to download and use, including for business (see LICENSE).

New: the OpenSEM app. Double-click opensem (or run opensem) and the app opens in your web browser. Everything runs on your own computer; nothing is uploaded.

New in 0.4: The OpenSEM App

• Four guided steps: Data, Model, Run, Results
• Load a CSV or TSV file by drag and drop, with a preview and missing-value count, or try the demo data
• Visual path diagram editor: add constructs, tick their items, connect paths by clicking, drag to arrange, reflective or formative; loops are refused
• Suggest Model groups items by name (T1, T2, T3 become construct T); Tidy Layout arranges the diagram
• Model text stays in sync with the diagram and can be edited directly
• Run with Auto Mode or choose method, estimator, resamples, confidence level, seed, group comparison and IPMA scale
• The full report opens in the app; Save Report keeps it as an HTML file
• Save Project and Open Project keep data, model and settings in one file
• Security: the app listens only on this computer, needs a secret per-session link, rejects other websites and uses a strict content security policy

New in 0.3: PLS-SEM Add-Ons

• PLSpredict: 10-fold cross-validation repeated 10 times, RMSE and MAE against a linear-model benchmark, Q2_predict, and the predictive-power verdict
• Multigroup analysis with --group <column>: permutation test of path differences (PLS-MGA) for every pair of groups
• MICOM measurement invariance: compositional invariance, equal means and equal variances
• Importance-performance map analysis (IPMA) for each final outcome construct

New in 0.2: CB-SEM

• Maximum likelihood estimation (Fisher scoring) with standard errors and the completely standardized solution
• Robust ML (Satorra-Bentler scaled chi-square and robust standard errors) for non-normal data
• FIML for missing data, compared against the EM saturated model
• Chi-square, CFI, TLI, RMSEA with 90% confidence interval and test of close fit, SRMR, AIC, BIC
• Modification indices with expected parameter change
• Bollen-Stine bootstrap model test and Mardia normality tests
• Residual covariances in the model syntax: x1 ~~ x2

New in 0.2: Mediation

• Specific and total indirect effects for CB-SEM and PLS-SEM, with bootstrap intervals (delta method under FIML)
• Mediation type for each indirect effect (complementary, competitive, indirect-only, direct-only, no effect)

Auto Mode

• Chooses CB-SEM for reflective models and PLS-SEM when a construct is formative
• Chooses ML, robust ML or FIML from the data, and falls back to PLS-SEM with an explanation if CB-SEM cannot be estimated

Still Included

• PLS path modelling and consistent PLS, reliability, AVE, HTMT, VIF, f squared, bootstrap on all CPU cores
• Self-contained HTML report with APA-style tables, a methods paragraph and the full reference list

Quick Start

1. Download the file for your system below and unzip it.
2. Double-click opensem (Windows: opensem.exe). The app opens in your browser; keep the small window open while you work.
3. Command line also works: opensem analyze --data mydata.csv --model mymodel.txt

Run opensem --help for the model syntax and all options. Each download has a .sha256 checksum. The macOS build is not notarised yet; if macOS blocks it, right-click the file and choose Open.

OpenSEM v0.3.0-alpha.1

OpenSEM 0.3: free CB-SEM and PLS-SEM software, written from scratch and backed by published research. Free to download and use, including for business (see LICENSE).

This is a command-line preview. The desktop app with a graphical interface comes in a later release.

New in 0.3: PLS-SEM Add-Ons

• PLSpredict: 10-fold cross-validation repeated 10 times, RMSE and MAE against a linear-model benchmark, Q2_predict, and the predictive-power verdict
• Multigroup analysis with --group <column>: permutation test of path differences (PLS-MGA) for every pair of groups
• MICOM measurement invariance: compositional invariance, equal means and equal variances
• Importance-performance map analysis (IPMA) for each final outcome construct

New in 0.2: CB-SEM

• Maximum likelihood estimation (Fisher scoring) with standard errors and the completely standardized solution
• Robust ML (Satorra-Bentler scaled chi-square and robust standard errors) for non-normal data
• FIML for missing data, compared against the EM saturated model
• Chi-square, CFI, TLI, RMSEA with 90% confidence interval and test of close fit, SRMR, AIC, BIC
• Modification indices with expected parameter change
• Bollen-Stine bootstrap model test and Mardia normality tests
• Residual covariances in the model syntax: x1 ~~ x2

New in 0.2: Mediation

• Specific and total indirect effects for CB-SEM and PLS-SEM, with bootstrap intervals (delta method under FIML)
• Mediation type for each indirect effect (complementary, competitive, indirect-only, direct-only, no effect)

Auto Mode

• Chooses CB-SEM for reflective models and PLS-SEM when a construct is formative
• Chooses ML, robust ML or FIML from the data, and falls back to PLS-SEM with an explanation if CB-SEM cannot be estimated

Still Included

• PLS path modelling and consistent PLS, reliability, AVE, HTMT, VIF, f squared, bootstrap on all CPU cores
• Self-contained HTML report with APA-style tables, a methods paragraph and the full reference list

Quick Start

1. Download the file for your system below and unzip it.
2. Run the demo: opensem demo
3. Run your own data: opensem analyze --data mydata.csv --model mymodel.txt

Run opensem --help for the model syntax and all options. Each download has a .sha256 checksum. The macOS build is not notarised yet; if macOS blocks it, right-click the file and choose Open.

OpenSEM v0.2.0-alpha.1

OpenSEM 0.2: free CB-SEM and PLS-SEM software, written from scratch and backed by published research. Free to download and use, including for business (see LICENSE).

This is a command-line preview. The desktop app with a graphical interface comes in a later release.

New in 0.2: CB-SEM

• Maximum likelihood estimation (Fisher scoring) with standard errors and the completely standardized solution
• Robust ML (Satorra-Bentler scaled chi-square and robust standard errors) for non-normal data
• FIML for missing data, compared against the EM saturated model
• Chi-square, CFI, TLI, RMSEA with 90% confidence interval and test of close fit, SRMR, AIC, BIC
• Modification indices with expected parameter change
• Bollen-Stine bootstrap model test and Mardia normality tests
• Residual covariances in the model syntax: x1 ~~ x2

New in 0.2: Mediation

• Specific and total indirect effects for CB-SEM and PLS-SEM, with bootstrap intervals (delta method under FIML)
• Mediation type for each indirect effect (complementary, competitive, indirect-only, direct-only, no effect)

Auto Mode

• Chooses CB-SEM for reflective models and PLS-SEM when a construct is formative
• Chooses ML, robust ML or FIML from the data, and falls back to PLS-SEM with an explanation if CB-SEM cannot be estimated

Still Included

• PLS path modelling and consistent PLS, reliability, AVE, HTMT, VIF, f squared, bootstrap on all CPU cores
• Self-contained HTML report with APA-style tables, a methods paragraph and the full reference list

Quick Start

1. Download the file for your system below and unzip it.
2. Run the demo: opensem demo
3. Run your own data: opensem analyze --data mydata.csv --model mymodel.txt

Run opensem --help for the model syntax and all options. Each download has a .sha256 checksum. The macOS build is not notarised yet; if macOS blocks it, right-click the file and choose Open.

OpenSEM v0.1.0-alpha.3

Preview of OpenSEM: free PLS-SEM software, written from scratch and backed by published research. Free to download and use, including for business (see LICENSE).

This is a command-line preview. The desktop app with a graphical interface comes in a later release.

What It Does

• Reads CSV / TSV data (comma, semicolon or tab; decimal comma; custom missing-value codes)
• PLS path modelling and consistent PLS (PLSc), reflective and formative constructs
• Reliability (Cronbach's alpha, rho_A, rho_c), AVE, HTMT, Fornell-Larcker, VIF, f², R²
• Bootstrap on all CPU cores (10,000 resamples by default, reproducible seed)
• Auto Mode: chooses the method, checks every result against published guidelines and explains it in plain language
• Self-contained HTML report with APA-style tables, a methods paragraph and the full reference list

Quick Start

1. Download the file for your system below and unzip it.
2. Run the demo: opensem demo
3. Run your own data: opensem analyze --data mydata.csv --model mymodel.txt

Run opensem --help for the model syntax and all options.

Each download has a .sha256 file so you can check it wasn't altered. The macOS build isn't notarised yet; if macOS blocks it, right-click the file and choose Open.