Comparison of analyses

From Jamovi english information
Jump to: navigation, search
SPSS (version 25, only covers functions from SPSS Standard; 2850$ / year)
Functions written red are part of the SPSS Base or those written blue are part of SPSS Advanced .
jamovi (versjon 1.1.5)
SPSS Analyze.png Jamovi Analyze.png

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.
Jamovi Modules.png

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