RESEARCH SUPPORT
Translating Analysis Between Software
Estimates Checked Against the Original Output
A finished analysis that has to run in a different program is re-specified in R, SPSS or Stata, its results compared estimate by estimate with the original, and each difference traced to a default, a rounding or a real error.
No Commitment Required
Strictly Confidential
In-House PhD-Level Statisticians
Fixed Project Fee
Same-Day Response
What Does Translating an Analysis Between Programs Involve?
Translating analysis between software means reproducing a model in a second program so that it returns the same estimates, which is a different task from retyping commands one for one. SPSS to R conversion and Stata to R translation both depend on defaults that differ: how missing values are dropped, which variance estimator is used, how a categorical predictor is coded and which sums of squares are reported. A translation is complete when the original estimates are reproduced to a stated precision and each remaining difference is explained. Within OnlineSPSS, a specialist statistical consultancy for academic, clinical and professional research, the translation stays with in-house PhD-level statisticians, and every default that was matched is recorded.
WHEN TO ENGAGE
Reasons a Finished Model Moves to Another Program
The reason an analysis has to move, whether a journal, a collaborator or a lapsing license, decides how closely the original must be matched.
Collaborators on Another Program A co-author or research group works in R or Stata, and the analysis built in SPSS must run there so that everyone on the project can inspect and extend it.
Open Code Requested A journal or funder asks for analysis code that can be shared, and the original was run through menus or in a program that reviewers are not able to open.
Replication Under Way A published analysis is being replicated in another program, and the task is to show whether the original numbers are reproduced and, if they are not, why.
Access Ending Access to the original program is ending, and the project needs its models moved to a new environment with results that can be defended as unchanged by the move.
WHAT MUST MATCH
Data, Model, Defaults and the Final Comparison
A translated model is judged by its numbers, so each stage of the work ends in a comparison with the original output.
Data and Missing Values
Variable types, labels, value codes and the treatment of missing values are carried over first, since different defaults for missing data alone can change the sample size.
Re-Specifying the Model
The model is re-specified from the design and the original output and not from the commands, with the coding of categorical predictors and reference groups made explicit.
Defaults That Differ
Each default that the programs do not share is identified and matched or documented, such as the variance estimator, the test for equal variances and the type of sums of squares.
Estimate-by-Estimate Check
Coefficients, standard errors, test statistics and intervals from both programs are compared at a stated precision, with the tolerance for agreement set before the comparison.
Other Environments
Routes from SAS, Python or other programs listed under Software follow the same comparison against the original output and the same record of matched defaults.
Reporting the Move
The methods section names the original and the new program with their versions and notes any difference that remains after the comparison, however small.
TRANSLATION PITFALLS
Differences That Change Results Between Programs
Two programs can run what looks like the same model and still disagree, because the disagreement sits in settings that neither output displays.
Reference Category Differs SPSS procedures often take the last category as the reference and R takes the first level by default, so coefficients look different though the model is the same.
Weights Mean Different Things A frequency weight in SPSS or Stata is not the weights argument of an R model fit, which treats weights as precision, so the standard errors diverge unless the weight type is matched.
Variance Estimator Not Shared Robust standard errors come in several versions, and the one Stata reports by default differs from the one many R functions return, so intervals differ slightly until they are matched.
Missing Values Handled Differently A missing value propagates through many R calculations but is dropped by default in many SPSS procedures, and Stata sorts missing numeric values above every real number, so a greater-than condition can include them.
Sums of Squares Types The anova function in R applied to a fitted model reports sequential sums of squares, whereas SPSS reports a different type by default, so tests of one model disagree when cells are unbalanced.
Percentile Definitions Quartiles and other percentiles can differ across programs because their definitions differ, which matters when a table reports an interquartile range.
DELIVERABLES
The Translated Analysis and the Evidence That It Matches
A collaborator who opens only these files can see what was matched, what was not and why, without rerunning the original program.
Translated Analysis Script The full analysis in the new program, organized in the order of the original and commented so that each model can be traced to its counterpart in the old code.
Comparison Ledger Original and translated estimates side by side for every reported model, with the difference and the tolerance applied to each line, so that agreement is visible at a glance.
Matched Defaults List Each setting that differs between the programs, how it was matched or why it could not be, and which of the two the reported results use for that setting.
Discrepancy Explanations For every remaining difference, the cause, such as a rounding rule or an algorithm, and a statement of whether it can affect any conclusion drawn from the models.
Data Dictionary Map A table linking each variable, label and value code in the original dataset to its form in the new one, including how missing values are represented.
Migration Methods Note Statistical wording for the move, naming both programs and versions and stating the precision at which results agree, matched to the output, for you to check and incorporate.
ILLUSTRATIVE EXAMPLE
Moving a Cohort Analysis From SPSS to R
An illustration of how a finished analysis is reproduced in a second program and the first disagreements are traced to their causes.
ILLUSTRATIVE EXAMPLE · CHILDHOOD LEAD EXPOSURE RESEARCH · UNITED STATES
A postdoctoral researcher in environmental health had analyzed a cohort in SPSS and needed the same analysis in R for a collaborating group and for a journal that asked for shareable code.
The first R run reproduced the descriptive tables and most coefficients but returned different coefficients for one categorical predictor and different standard errors overall. The comparison traced both causes: the SPSS model took the last category as the reference while the R model took the first, and the original analysis used a frequency weight that R’s modeling function read as a precision weight. After the weight was handled correctly and the reference group matched, the estimates agreed at the stated precision. One small difference remained, from the variance estimator, and it was documented. The researcher decided which version to report.
Outcome: The researcher received the R script, the comparison ledger, the list of matched defaults, the explanation of the remaining difference and a methods note naming both programs and versions.
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
Reproducing One Model in SPSS, Stata and R
Any of these programs can be the source or the target of a translation, and what matters is which settings each makes visible.
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
Which Version to Report Is the Author's Decision
When two programs differ, the translation explains why, and the choice of what appears in the paper is made by the author.
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 research. Authorship of the article or report remains yours.
Your Research Decisions The original model, the choice of the program used for the reported results, the interpretation of the findings 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
Moving an Analysis Between Programs
A translated result can stand in for the original only when the converter's output is checked, a tolerance for agreement is set and the methods section names the program used.
What does translating analysis between software involve?
Translating analysis between software involves re-specifying a finished model in another program, matching the settings that differ, and comparing every estimate with the original output until they agree or the difference is explained. It covers moves such as SPSS to R and Stata to R, and the result is a script plus a record of what was matched.
How is it confirmed that the translated analysis reproduces the original?
The original output is the reference. Coefficients, standard errors, test statistics and intervals are compared model by model at a precision set beforehand, usually a fixed number of decimal places. Where a value disagrees, the cause is traced to a default, a rounding rule or an error, and the comparison is repeated until each difference is accounted for.
Can SPSS syntax be converted to R code automatically?
Simple commands can be mapped one for one, but a mapping does not reconcile defaults, so the converted code can run without error and still return different numbers. For that reason the model is re-specified from the design and the output, and the result is checked against the original, not accepted because the code ran.
Does the translated analysis have to be reported as a new analysis?
The methods section should name the program and version used for the reported results. If the numbers match the original, the paper may report the translated analysis and say that it reproduces the earlier one. If they differ, the report states which version is used and why, so that readers are not left to find the discrepancy.
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 original syntax, the output and the dataset, 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
Which Numbers Must
the New Program Reproduce?
Naming the original output as the reference, and the precision at which the new results must agree with it, settles what a translation has to match.
No Commitment Required
Strictly Confidential
Fixed Project Fee
In-House PhD-Level Statisticians
Same-Day Response
Serving Researchers Since 2014