RESEARCH SUPPORT
jamovi support for models
beyond the default menus
Jamovi modules for analysis, such as GAMLj, take jamovi beyond its base menus to mixed and generalized linear models, with each model checked against your design, its settings recorded and the tables prepared for a manuscript in APA style.
No Commitment Required
Strictly Confidential
In-House PhD-Level Statisticians
Fixed Project Fee
Same-Day Response
What Does jamovi Support Cover Beyond the Menus?
jamovi support at OnlineSPSS is help with the analysis you are running in jamovi, aimed at the point where the base menus stop fitting a design with clustered observations, repeated measures, counts or an interaction to probe. It is research-analysis support, not vendor support, installation or licensing help. Choosing a module such as GAMLj, checking the defaults behind the output and preparing the tables for APA reporting fall to an in-house PhD-level statistician at OnlineSPSS, a specialist statistical consultancy for academic, clinical and professional research. Module authors maintain their own releases, so options differ between versions and the versions used are recorded. Where a model outgrows what a module offers, the analysis moves to R or another program that can fit it.
WHEN TO ENGAGE
Designs That Reach Past the Base Menus
The base analyses suit a single-level comparison or regression, and a project crosses that boundary when its design adds clusters, repeated measures, counts or an interaction that needs probing.
Repeated Measures, Missed Visits Some participants miss occasions, so a repeated-measures ANOVA would drop them, and a mixed model that keeps every observed measurement is considered in its place.
Children Within Classrooms Observations are nested in groups, and an ordinary regression would treat them as independent, so a random-effects structure for the groups has to be specified and checked.
A Count or Yes-No Outcome The outcome is a count or a binary response and a linear model does not fit it, so a generalized linear model with a suitable distribution and link is selected.
An Interaction to Probe A moderator changes the effect of a predictor, and simple slopes with plots of the interaction are needed to show where the effect holds and where it does not.
MODULES AND LIMITS
Modules, Models and Their Limits
Each module covers a family of models, and knowing where its options end matters as much as knowing what it fits.
GAMLj Linear Models
GAMLj's general linear model analysis in Jamovi handles regression and ANOVA designs with factors and covariates, with simple effects and plots for interactions.
Mixed-Effects Models
GAMLj's mixed model analysis fits random intercepts and slopes for nested or repeated data, as discussed for Linear Mixed Models (Multilevel Modeling), within the options it exposes.
Generalized Linear Models
Logistic, Poisson and related models are fitted for binary and count outcomes, and the exponentiated coefficients are reported with their confidence intervals.
Mediation and Other Modules
Further modules add mediation models and meta-analytic pooling, and each is checked for what it estimates, since module options and defaults vary by version.
Limits of the Interface
Complex correlation structures, custom estimators and scripted pipelines are harder in a menu-driven program, and the point at which jamovi stops being the right tool is stated.
Moving to Other Software
When a model exceeds a module, the analysis is carried to R or another program, or to JASP for a Bayesian counterpart, and the results are compared.
SETUP CAVEATS
Output That Looks Settled but Is Not
Module output looks equally finished whether or not the model suits the design, which is why the setup is read before the estimates.
Random Effects Left Out A repeated or clustered design is analyzed with fixed effects only, which treats related observations as independent and gives intervals that are too narrow.
Degrees of Freedom Unstated A mixed model's p-values depend on how denominator degrees of freedom are approximated, and a report that omits the method hides something that can matter for borderline results.
Covariate Scaling Overlooked Covariates may be centered or standardized by the module's scaling option, so a factor effect in a model with an interaction is read at the covariate value the setting implies, and the setting is reported.
Convergence Warnings Ignored A singular or non-converged mixed model is reported as if it were estimated well, although the warning signals a random-effects structure the data cannot support.
Module Version Unreported Modules are updated separately from jamovi, so the report names the jamovi and module versions used, because defaults and options can change between releases.
Tables Pasted Without Checking Output tables are copied as formatted, though the target style asks for effect sizes, intervals and a stated test for each model, which the default output may not supply.
DELIVERABLES
Module Analysis Handover Files
Every table in the manuscript is paired with the module, version and settings that produced it.
Saved Analysis File The jamovi file with the data and every analysis in order, so that the output can be reopened and checked by a coauthor or supervisor.
Release and Settings Log The versions of jamovi and each module used, with the settings that affect results, such as the degrees-of-freedom method and the contrast coding.
Model Specification Note A short note explaining the choice of module, the fixed and random terms, the distribution and the assumptions examined, in the terms of your design.
Model-Check Summary Residual plots, convergence information and influence checks, with a comment on whether the results hold when the model is simplified.
Tables for APA Reporting Tables with estimates, confidence intervals and effect sizes in APA style, adapted from the output for the manuscript or thesis.
Notes for Later Reruns Instructions for reopening and extending the analysis in jamovi, and for where Quantitative Data Analysis takes over beyond it.
ILLUSTRATIVE EXAMPLE
Swimmers, Clubs and a Singular Fit
An illustration of how repeated measurements from athletes grouped in clubs are modeled in a jamovi module and simplified when the data cannot support the requested structure.
ILLUSTRATIVE EXAMPLE · YOUTH SWIM CLUB TRAINING RESEARCH · UNITED STATES
A master's researcher in sport science compared sprint times at three points in a season between young swimmers who chose a new dryland training plan and teammates who kept the usual program, across a handful of clubs.
Times were repeated within swimmers and swimmers were grouped in clubs, so the plan was a mixed model in the module with random intercepts for swimmer and club and a time-by-plan interaction. The complication was the output: the fit was flagged as singular, because the small number of clubs could not support a separate variance for club. Club was entered as a fixed factor instead, the simpler structure was reported, the denominator degrees-of-freedom method was named, and the jamovi and module versions were recorded. The difference in change between plans was reported with its interval, and because swimmers chose their own plan, it was worded as an association, not as an effect of the training.
Outcome: The researcher received the difference in change between plans with its 95% confidence interval, the swimmer-level variance, the saved jamovi file, the version record, APA-style tables and a note on how to report the simplified model, for the researcher to check and incorporate.
This example does not describe a real client or project. We never share details of actual client work, in line with the confidentiality we promise every researcher. This illustrative example is included to show the type, scope, and standard of work involved in this kind of analysis.
SOFTWARE
When the Model Outgrows jamovi: R, SPSS, SAS and Stata
A mixed or generalized model that exceeds a module's options is fitted in a program with fuller control, and the results are compared with the jamovi output.
HOW WE ASSESS YOUR PROJECT
We Review Your Actual Research
Your assessment is based on a review of your actual research materials and analytical requirements, not a generic project category.
You Submit Your Project Details
Share whatever is available at the current stage, such as the research aim, protocol or proposal, dataset, variable list, manuscript or statistical requirements.
We Review Your Research and Define the Scope
Your statistically trained Research Coordinator reviews the materials to understand the study design, research questions, data structure, analytical requirements and expected deliverables. If clarification is needed, additional documents or information can be requested before the assessment is finalized.
Your Analysis Is Completed and Delivered
Once the scope and fixed project fee are agreed, the in-house statistician completes the work and the Research Coordinator remains the communication point through delivery, with the analysis, deliverables and timeline as agreed.
RESEARCH RESPONSIBILITY
Hypotheses and Meaning Rest With the Researcher
Which hypotheses were planned and what the estimates mean for the study's question are decisions for the researcher, taken with the output in hand.
Agreed Statistical Support OnlineSPSS provides the agreed methodological, analytical and statistical reporting support, defined in a scope that is confirmed before any work begins.
No Intellectual Contribution OnlineSPSS does not claim any intellectual contribution to your thesis, article or report. Authorship remains the researcher's.
Your Research Decisions The research question, the hypotheses, the substantive meaning of the estimates, the discussion and the conclusions remain yours, with overall responsibility.
Confidential Handling Research data and project details are handled confidentially, project information is not published, and an NDA is available where required.
FREQUENTLY ASKED QUESTIONS
Questions About jamovi Modules and Mixed Models
The jamovi tables look close to finished, yet a reviewer, a coauthor without the modules or a refit in R may find what they leave out.
Where can I get jamovi help for a model the menus do not offer?
Jamovi help for a model beyond the default menus means choosing a module such as GAMLj, fitting the model to your design, and recording the settings and versions behind the results. Beyond the menus, how to use jamovi for data analysis becomes a question of model choice and defaults, which is where this support starts. A project may use one module or several, for instance GAMLj for the main model and another module for a mediation path.
Does a GAMLj mixed model give the same estimates as lme4 in R?
It should, given the same data and settings, because GAMLj fits its mixed models with the lme4 package underneath. Apparent differences usually come from the module’s own defaults, such as the contrast coding of factors, the scaling of covariates or the degrees-of-freedom method, so these settings are recorded and matched when the model is refitted in R for a reviewer or coauthor.
Does jamovi output follow APA style as it stands?
Tables are laid out in a form close to APA style, but a manuscript needs more than the layout. APA 7 reporting expects effect sizes, confidence intervals, exact p-values and degrees of freedom where relevant, and the statistical test named. The output is checked against those requirements and adapted, not pasted unchecked.
Can a coauthor reopen my analysis if the modules are not installed?
A saved analysis generally needs a jamovi installation that has the modules it used, and results can differ if their versions differ. The handover therefore lists the jamovi and module versions, and the main tables are also supplied as separate files, so a coauthor without the modules can still read the results.
How do you protect my research data and confidentiality?
Your data and project details are handled confidentially, and project information is not published. Researcher names and institutions are not used publicly without permission. An NDA is available where required and can be arranged before sensitive materials are shared. Read more about confidentiality and data security.
What happens when I request an assessment, and how long does it take?
You share your research question, design and relevant materials, such as the dataset, any jamovi files, the output tables you already have and the model your design calls for, and a statistically trained Research Coordinator reviews the request and responds the same day. The analysis, deliverables, timeline and one fixed project fee are then confirmed before any work begins, so the timeline follows from the agreed scope.
Still have a question? Find more answers in our full FAQ.
NEXT STEP
Check Whether a Module
Fits Your Design
Some designs sit comfortably inside a jamovi module and others reach its edge, so the first statistical question is which kind your study is.
No Commitment Required
Strictly Confidential
Fixed Project Fee
In-House PhD-Level Statisticians
Same-Day Response
Serving Researchers Since 2014