Comparison of analyses
From Jamovi english information
SPSS (version 25) The overview covers functions from SPSS Base (99$) and Advanced (79 US$), i.e. 178 US$ / user and month. |
jamovi (versjon 1.2) |
Already at first glance, it becomes clear that jamovi has fewer features than SPSS. But: [1] There is a (increasing) number of features made available via modules (press the "+" sign in the right upper corner of the jamovi window to add them) and [2] The features implemented already cover "standard" needs (90% of the most common analyses used in psychology). Feel free to check out which modules are available: There is also quite a wealth of modules covering functions that are not available in SPSS but very useful (eg for meta-analyses; MAJOR). And if you are willing to use some R code (in conjunction with the jamovi-module Rj) then you can (most presumably) do every analysis you could imagine. | |
Reports | |
Reports → Codebook | N/A |
Reports → OLAP Cubes | N/A |
Reports → Case summaries | Exploration → Descriptives has the same functionality |
Reports → Reports Summaries in Rows | N/A |
Reports → Reports Summaries in Columns | N/A |
Descriptive Statistics | |
Descriptive Statistics → Frequencies | Exploration → Descriptives, tick «Frequency tables» to get an output that is similar to that of «Frequencies» in SPSS |
Descriptive Statistics → Descriptives | |
Descriptive Statistics → Explore | |
Descriptive Statistics → Crosstabs | Frequencies → (Contingency tables) → Independent samples |
Descriptive Statistics → Ratio | N/A |
Bayesian Statistics | |
requires the jamovi-module «jsq» | |
Bayesian Statistics → One Sample Normal | T-Test → Bayesian One Sample T-Test |
Bayesian Statistics → One Sample Binomial | Frequencies → Bayesian Proportion Test |
Bayesian Statistics → One Sample Poisson | Frequencies → Bayesian Contingency Tables |
Bayesian Statistics → Related Sample Normal | T-Test → Bayesian Paired Samples T-Test |
Bayesian Statistics → Independent Samples Normal | T-Test → Bayesian Independent Samples T-Test |
Bayesian Statistics → Pearson Correlation | Regression → Bayesian Correlation Matrix Regression → Bayesian Correlation Pairs |
Bayesian Statistics → Linear Regression | Regression → Bayesian Linear Regression |
Bayesian Statistics → One-way ANOVA | ANOVA → Bayesian ANOVA (can handle several factors while SPSS is limited to one factor) |
Bayesian Statistics → Log-Linear Models | Frequencies → Bayesian Log-Linear Regression |
Compare Means | |
Compare Means → Means... | Exploration → Descriptives replaces / integrates that functionality, choose the drop-down menu «Statistics» and set ticks at «Mean», «N» and «Std. deviation» |
Compare Means → Independent-Samples T Test | T-Test → Independent Samples T-Test |
Compare Means → Paired-Samples T Test | T-Test → Paired Samples T-Test |
Compare Means → One-Sample T Test | T-Test → One Sample T-Test |
Compare Means → One-Way ANOVA | ANOVA → One-Way ANOVA |
General Linear Model | |
General Linear Model → Univariate | ANOVA → One-Way ANOVA |
General Linear Model → Multivariate | ANOVA → MANCOVA |
General Linear Model → Repeated Measures | ANOVA → Repeated Measures ANOVA |
General Linear Model → Variance Components | N/A |
Generalized Linear Models | |
requires the jamovi-module «GAMLj» (General Analyses for the Linear Model in Jamovi) | |
Generalized Linear Models → Generalized Linear Models | |
Generalized Linear Models → Generalized Estimating Equations | |
Mixed Models | |
requires the jamovi-module «GAMLj» (General Analyses for the Linear Model in Jamovi) | |
Mixed Models → Linear | |
Mixed Models → Generalized Linear | |
Correlate | |
Correlate → Bivariate | Regression → Correlation Matrix |
Correlate → Partial | N/A, can be calculated using R-code and the R-libraries «ppcor» or «psych» |
Correlate → Distances | N/A, can be calculated using R-code |
Regression | |
Regression → Automatic Linear Models | Create a standard model. → Enhance model accuracy (boosting). → Enhance model stability (bagging). |
Regression → Linear | Regression → Linear Regression |
Regression → Ordinal | Regression → (Logistic Regression) → Ordinal Outcomes |
Regression → Curve Estimation | |
Regression → Partial Least Squares | |
Loglinear | |
Loglinear → General | Frequencies → Log-Linear Regression |
Loglinear → Logit | |
Loglinear → Model Selection | |
Classify | |
Classify → Nearest Neighbor | N/A |
Classify → Discriminant | N/A, can be calculated using R-code and the R-library «MASS» |
Classify → TwoStep Cluster | N/A |
Classify → Hierarchical Cluster | N/A, can be calculated using R-code and the R-library «pvclust» |
Classify → K-Means Cluster | N/A, can be calculated using R-code |
Dimension Reduction | |
Dimension Reduction → Factor | Factor → (Data reduction) → Principal Component Analysis Factor → (Data reduction) → Exploratory Factor Analysis the main difference is that «Exploratory Factor Analysis» offers more options for factor extracton |
Scale | |
Scale → Reliability Analysis | Factor → (Scale analysis) → Reliability analysis |
Scale → Multidimensional Scaling | N/A |
Nonparametric Tests | |
Nonparametric Tests → One Sample | N/A, the tests itself are available (see below), but not the start menu that allows a selection based on your data (e.g., between- or within-subject) |
Nonparametric Tests → Independent Samples | N/A, the tests itself are available (see below), but not the start menu that allows a selection based on your data (e.g., between- or within-subject) |
Nonparametric Tests → Related Samples | N/A, the tests itself are available (see below), but not the start menu that allows a selection based on your data (e.g., between- or within-subject) |
Nonparametric Tests → Legacy Dialogs → Chi-Square | Frequencies → (One Sample Proportion Tests) → N Outcomes (x² goodness of fit) |
Nonparametric Tests → Legacy Dialogs → Binomial | Frequencies → (One Sample Proportion Tests) → 2 Outcomes (Binomial test) |
Nonparametric Tests → Legacy Dialogs → Runs | N/A |
Nonparametric Tests → Legacy Dialogs → 1-Sample K-S | N/A, Shapiro-Wilks available under Exploration → Descriptives, choose drop-down menu «Statistics» and tick «Shapiro-Wilks» |
Nonparametric Tests → Legacy Dialogs → 2 Independent Samples | T-Test → Independent Samples T-Test, set kryss/tikk på «Mann-Whitney U» |
Nonparametric Tests → Legacy Dialogs → 2 Related Samples | T-Test → Paired Samples T-Test, set kryss/tikk på «Wilcoxon Rank» |
Nonparametric Tests → Legacy Dialogs → K Independent Samples | ANOVA → (Non-Parametric) → One-Way ANOVA (Kruskal-Wallis) |
Nonparametric Tests → Legacy Dialogs → K Related Samples | ANOVA → (Non-Parametric) → Repeated Measures ANOVA (Friedman) |
Survival | |
requires the jamovi-module «Death watch» | |
Survival → Life Tables | |
Survival → Kaplan-Meier | |
Survival → Cox Regression | |
Survival → Cox w/ Time-Dep Cov | |
Multiple Response | |
Multiple Response → Define Variable Sets | N/A |
Multiple Response → Frequencies | |
Multiple Response → Crosstabs | |
ROC Curve | |
ROC Curve | N/A, accessible via R packages (f.eks., ROCR eller pROC) |
Simulation | |
Simulation | N/A |
Spatial and Temporal Modeling | |
Spatial and Temporal Modeling → Spatial Modeling | N/A |