Comparison of analyses

SPSS (version 25) The overview covers functions from SPSS Base (99$) and Advanced (79 US$), i.e. 178 US$ / user and month. Functions written red are part of the SPSS Base or those written blue are part of SPSS Advanced .	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