STATISTICAL SOFTWARE
Jamovi Data Analysis Service
Traceable Analysis in Open-Source Software
Our Jamovi data analysis service carries out comparisons, regression and factor analysis in Jamovi, working from your data files and .omv projects, with the project file and the module settings documented where agreed so that every result can be traced and rerun.
No Commitment Required
Strictly Confidential
In-House PhD-Level Statisticians
Fixed Project Fee
Same-Day Response
What Is Jamovi Used For in Research?
Jamovi is a free, open-source statistical spreadsheet built on R, with a point-and-click interface and analyses organized in modules. Researchers choose it for common comparisons, regression and factor analysis in a tool that supervisors, coauthors and collaborators can all install, and because results update as the settings change. That convenience has a cost: the way each variable is typed and the defaults of each module decide which model is run, and both are easy to miss. OnlineSPSS, a specialist statistical consultancy for academic, clinical and professional research, provides a Jamovi data analysis service in which an in-house PhD-level statistician carries out the agreed analysis in Jamovi, working from your files and recording the settings so that you can rerun it.
WHEN TO ENGAGE
Four Situations That Bring Us a Jamovi Project
Jamovi statistical analysis is requested at different stages: before anything is run, when output looks wrong, when a project file exists or when a reviewer asks questions.
Analysis Planned, Not Yet Run The comparison or model is fixed in your plan and the data sit in a Jamovi file, and the work is to run it with correct variable types and report effect sizes and confidence intervals, not significance statements alone.
Output That Looks Wrong A test offers unexpected options, a categorical variable behaves like a number or the degrees of freedom are not what the design implies, and the cause has to be found in how the data were typed.
An .omv Project to Check A doctoral researcher's or coauthor's .omv project needs checking or extending, and Jamovi consulting here means reading the settings stored in the project, not judging the results table alone.
Supervisor or Reviewer Query A supervisor or reviewer asks which tests, modules and options produced a reported result, so the analysis has to be rerun, documented and reported with the software and module versions.
ANALYSES IN JAMOVI
Analyses Carried Out in Jamovi for Your Study Design
Jamovi ANOVA, regression and factor analysis requests start from the study design, and each card below links to the method page where the choice of approach is explained.
Independent Samples t-Test
Two independent groups are compared with Welch's test unless equal variances can be justified, reporting the mean difference, its 95% confidence interval and an effect size with its own interval.
One-Way ANOVA
Differences between three or more groups are tested with Welch's F unless the design justifies equal variances, then followed by post hoc comparisons that carry a multiplicity correction.
Multiple Linear Regression
Predictors are entered with their types and factor coding confirmed, and coefficients are reported with confidence intervals beside residual and collinearity diagnostics.
Logistic Regression
A binary outcome is modeled with the reference level of the outcome and of each factor stated, because those settings decide which odds ratio Jamovi prints, and every ratio is reported with its interval.
Exploratory Factor Analysis (EFA)
Item adequacy is checked before extraction, the number of factors is judged from parallel analysis and interpretability, and the rotation is stated and justified.
Reliability Analysis (Cronbach's Alpha)
Scale reliability is reported after reverse-keyed items are recoded, with an interval, and with omega added where the items cannot be assumed to load equally.
COMMON JAMOVI ISSUES
Where Jamovi Analyses Go Wrong Before the Result
A point-and-click analysis always produces output, so the errors that matter are the quiet ones, and each check below is made before a result is reported.
Variable Types After Import A Likert item imported as nominal or an ID read as continuous changes which tests are offered and how they are computed. Each type is compared with the codebook before any analysis.
Factor Coding and Contrasts The reference level and contrast coding decide what a coefficient means, so they are stated, and changed on purpose where the default does not answer your question.
Missing-Data Behavior Modules differ in how they exclude cases with missing values, so the number of cases behind each result is counted, and the pattern of missingness is examined before estimates are trusted.
Module Defaults Behind the Menu Defaults such as the sums-of-squares type, the variance assumption or the post hoc correction are read from the settings and justified, not accepted because output appeared.
Values Edited in the Spreadsheet Jamovi lets values be typed over directly in the data view, and a corrected value leaves no trace in the output, so changes are made as recoded or computed variables and logged against the original file.
Computed Variables and Filters Computed scores, reverse-keyed items and filters are checked against the source values, because a filter left active removes cases from every analysis without a warning.
DELIVERABLES
What You Receive From a Jamovi Analysis
The files follow a documented Jamovi project, agreed in the scope and provided where applicable, so that you can reopen the work and see how each result was produced.
Saved .omv Project The saved .omv project holds the data, the analyses and their settings together, so the work can be reopened and checked step by step.
Module and Version Record Each module used and the Jamovi version are recorded, so that a coauthor or reviewer can rebuild the same setup before rerunning anything.
Cleaned Data and Codebook A cleaned data file with correctly typed variables and labels, plus a codebook of recodes, computed variables and every filter applied.
Tables and Figures Publication-ready tables and figures rebuilt from the Jamovi output in the format agreed, with effect sizes, confidence intervals and the number of cases behind each.
Statistical Interpretation Each result is interpreted as the comparison or model your design supports, with the limits that follow from coding, missing cases or sample size named plainly.
R Syntax Where Agreed Where agreed, the R syntax that Jamovi shows for an analysis is supplied beside the project, so the work can also be rerun outside Jamovi.
OTHER PLATFORMS
When Another Platform May Be More Appropriate
Jamovi fits analyses that its modules cover and that a team can reopen without writing code, and some projects are better served elsewhere.
ILLUSTRATIVE EXAMPLE
How a Jamovi Analysis May Look in Practice
An illustration of how a classroom comparison moves from a mistyped variable to a result a coauthor can reopen.
ILLUSTRATIVE EXAMPLE · SECOND LANGUAGE ACQUISITION RESEARCH · UNITED STATES
A university language-learning group compared vocabulary retention under three instructional conditions, using pretest and delayed posttest scores kept in one spreadsheet and analyzed in Jamovi by several coauthors.
The analysis plan fixed the delayed posttest as the outcome and the pretest as a covariate before any model was fitted. The first run treated the condition column, coded 1, 2 and 3, as a continuous predictor, so the model estimated a single slope instead of two group differences. The variable was retyped as nominal against the codebook, the reference condition was stated, and the model was refitted with the pretest slope checked for equality across conditions. The module defaults for sums of squares and post hoc correction were read from the settings, and the saved project was annotated so that each choice could be seen by a person opening it later.
Outcome: The group received the adjusted mean differences between conditions with their 95% confidence intervals and effect sizes, the .omv project, a record of the modules used and a codebook of the recoding.
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.
RESEARCH DISCIPLINES
Research Fields Where Jamovi Is Common
Jamovi is often used in psychology, education and the social sciences, where a free tool suits doctoral researchers and small teams, and the same typing and coding questions arise wherever groups or scales are analyzed.
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.
RESEARCHER VOICE
What Researchers Say
Feedback from an academic researcher on variables imported with the wrong type and a workflow that could be rerun instead of screenshots.
“Our issue with Jamovi was not the interface itself; it was variables being imported with the wrong continuous, ordinal, or nominal type. They worked directly with the files we already had and left us with a much cleaner, reproducible workflow rather than just screenshots of output.”
Statistical Support Within Your Research OnlineSPSS provides the agreed methodological, analytical and statistical reporting support, including the Jamovi files described in the scope. The researcher or research team retains the scientific question, substantive interpretation, conclusions and overall responsibility for the research.
FREQUENTLY ASKED QUESTIONS
Questions About Jamovi Analysis for Research
Short answers to what researchers ask before sharing a Jamovi project, from the analyses we run and existing .omv files to reproducibility, model limits and confidentiality.
Which parts of my study can be analyzed in Jamovi?
Most group comparisons, regression models and scale analyses can: Jamovi research statistics at OnlineSPSS covers t-tests, ANOVA, linear and logistic regression, factor analysis and scale reliability. The choice follows your research question and design, and it is confirmed during the assessment.
Will you open my .omv file as it is, or rebuild the analysis?
We open it as it is. Variable types, filters and the settings of every analysis are read before anything is changed or added, and a finished analysis can also be checked through Independent Statistical Review, which names what holds and what needs correcting.
How do you keep a point-and-click analysis reproducible?
The saved project, the modules and the settings of each analysis are documented, so that another person can reopen the work and see how every result was produced. Screenshots of output are not treated as a record of the analysis. Where agreed, R syntax is supplied so the analysis can also be rerun outside Jamovi.
What if my model needs more than Jamovi's modules offer?
Often an add-on module from the Jamovi library covers it, for example GAMLj for mixed models or jAMM for mediation, and the module is then named in the delivered record. Where no module fits the model, the assessment says so and the work is agreed in R instead.
How do you protect my research data and confidentiality?
Your datasets and Jamovi projects are handled confidentially, and project information is not published. 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 and any existing project file, 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.
Still have a question? Find more answers in our full FAQ.
NEXT STEP
Discuss Your
Jamovi Analysis With Us
Send the research question, the data file and any .omv project you already have. We review how the variables are typed and which modules are needed before any work begins.
No Commitment Required
Strictly Confidential
Fixed Project Fee
In-House PhD-Level Statisticians
Same-Day Response
Serving Researchers Since 2014