RESEARCH SUPPORT
Data Analysis Support Before the First Model
A Dataset Ready and a Plan Agreed
Before the first model is fitted, preparing data for statistical analysis settles the unit of analysis, types and scores the variables, structures the file for the design and agrees an analysis plan with you, so that the output answers questions set in advance.
No Commitment Required
Strictly Confidential
In-House PhD-Level Statisticians
Fixed Project Fee
Same-Day Response
What Makes a Dataset Ready to Analyze?
Data analysis support begins before any model is fitted, by establishing what the dataset is: its unit of analysis, the way rows relate to one another and the measurement scale of each variable, because those facts decide which analyses are valid. Producing an analysis-ready dataset brings the source file into that form, with data cleaning before analysis recorded step by step. A research data analysis plan then fixes the questions, outcomes, models and handling of gaps before any output is inspected. For OnlineSPSS, a specialist statistical consultancy for academic, clinical and professional research, this preparation is PhD-level statistical work done in-house, and the plan is agreed with you. The analysis that follows, and what it means for your field, are yours to interpret and to report.
WHEN TO ENGAGE
Signs a Dataset Is Not Ready Yet
The preparation is worth doing carefully when the file was built for another purpose or its structure has never been described, and the plan follows from what it shows.
A Spreadsheet Built for Entry The file was laid out for data entry or for a different report, so its columns and blank cells do not correspond to the variables the study needs.
Rows With Different Meanings Some rows are participants, some are visits and some are tests, and no one has said which unit the analysis should treat as independent.
Several Sources, One Study Survey, record and laboratory files describe the same people or sites, and the links between them have to be established before any combined analysis.
No Plan Beyond the Software The analysis exists as a list of procedures in a program, and the researcher wants questions, outcomes and models set out in a plan that can be defended.
PREPARATION AND PLAN
From Source File to Agreed Plan
The file is shaped to the design first, and the plan is then built on what the prepared file can actually support.
What a Row Represents
The entity each row represents is settled, together with the ones that are linked, such as repeated visits to one person, because this decides the independence of observations.
File Layout
The file is arranged in wide or long form as the analysis requires, and clusters, repeated measures and matched pairs are identified so that the structure is available to the model.
Typing and Scoring
Each variable is typed as nominal, ordinal or numeric, scales are scored by their stated rule, and reverse-keyed items are handled before any totals are formed.
Gaps in the Data
Blank cells are separated into not asked, not applicable and not answered, and the handling of absent values follows the approaches of Missing Data Analysis.
The Analysis Plan
Each question is tied to an outcome, a model and an estimate, with primary and secondary analyses distinguished, as part of Quantitative Data Analysis.
Handover to Analysis
The prepared file and the plan pass to the analysis stage and then to Results Reporting & Interpretation, two of the stages described among the Services.
PREPARATION FAULTS
Faults a Prepared Dataset Avoids
These faults are built into a file before any model exists, and each one changes an estimate or its interval without producing an error message.
Repeated Rows Read as Independent Several rows per participant are analyzed as if each came from a different person, which makes the standard errors too small and the intervals too narrow.
Codes Averaged as Numbers Category codes for a nominal variable are treated as numeric, so an average of the codes is computed that has no meaning in the units of the study.
Reverse-Keyed Items Missed A scale total is built without reversing negatively worded items, so the score mixes opposite directions and its reliability is lower than it should be.
One Blank, Several Meanings A blank cell may mean not asked, refused or zero, and treating all blanks alike turns a skip pattern into a missing-data problem or a false zero.
Wide File, Long Model A file with one column per time point is passed to a model that expects one row per measurement, and the program quietly uses only part of the data.
A Plan Fixed After the Output Questions are refined once results are visible, so primary and secondary analyses can no longer be told apart, and the choice of tests cannot be justified.
DELIVERABLES
Documents That Describe the Data and the Plan
The items fix what the file contains and what will be done with it, so that the analysis stage rests on agreement and not on assumption.
Variable Definitions Sheet Every variable with its type, scale, units, allowed values, scoring rule and source, so that anyone can read the file without asking its author.
Data Structure Memo A short statement of the unit of analysis, the links between rows and the clustering or repetition the models must respect.
Prepared Dataset The file in the structure the planned analyses need, in the format of your program, with value labels and missing-value codes declared.
Missing-Value Summary The extent and pattern of absent values by variable and group, with the proposed handling and the assumption on which it depends.
Agreed Analysis Plan Each question with its outcome, model, diagnostics and decision rules, and a clear division between primary, secondary and exploratory analyses.
Build Script The commands that convert the source file into the prepared dataset step by step, so the preparation can be repeated if the source changes.
ILLUSTRATIVE EXAMPLE
Shelter Records Joined to an Adopter Survey
An illustration of how an entry spreadsheet and a linked questionnaire were prepared and planned before any comparison was run.
ILLUSTRATIVE EXAMPLE · ANIMAL SHELTER ADOPTION RESEARCH · UNITED STATES
A researcher at a veterinary school wanted to relate the way animals were housed before adoption to adopters' later satisfaction, using shelter intake records and a follow-up questionnaire completed by adopters.
The intake sheet had been laid out for staff, with merged headers, notes typed into cells and housing codes that changed partway through the period, so the first task was a variable definitions sheet that fixed one meaning for every column. The questionnaire was linked to the records by adoption number, and unmatched cases were listed, not dropped. The complication was a skip pattern: questions about a second pet were asked only of adopters who had one, so blanks from adopters without one meant not applicable rather than missing. Two satisfaction items were negatively worded and were reversed before the scale was scored, and the plan fixed the primary outcome and stated the housing comparison as an association before any model was fitted.
Outcome: The researcher received the variable definitions sheet, the data structure memo, the linked and scored dataset, the missing-value summary, the analysis plan and the build script that produced the file from both sources.
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
Reshaping and Typing Data in Practice
Reshaping, labeling and merging are routine in each of these programs; what matters is that the steps are saved as code that a colleague can rerun.
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
Research Questions Set the Terms of the File
The file and the plan are prepared with you, and the research questions they serve, and the reading of the results, are for the researcher to decide.
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 report, thesis or article remains yours.
Your Research Decisions The research questions, the definition of each variable, the choice among the plans proposed 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
Getting a File and a Plan Ready
Plans that need amending, files in the wrong layout and spreadsheets built for typing are where preparation usually starts.
Where can I get data analysis support online?
A researcher can request an assessment from OnlineSPSS online, share the source files and receive support in preparing data for statistical analysis: the dataset shaped to its design, a variable definitions sheet and an agreed analysis plan. The analysis and reporting that follow are optional, so a project may use the preparation and the plan alone.
Can the analysis plan change once the work has started?
It can, if the reason is recorded: a variable that proves unreliable, a model the data cannot support or a structure the file turned out not to have. The change is dated, the original intention stays visible in the plan, and analyses added after results were seen are labeled exploratory.
Does my file need to be in wide or long format?
It depends on the analysis and the program. Models for repeated measurements usually expect one row per measurement, while some procedures expect one row per participant. The structure memo records the form each planned analysis needs, and the build script converts between them.
Can you work from a spreadsheet laid out for data entry?
Yes. Many research files begin that way, with merged headers, notes inside cells and codes that vary between columns. The first step is to describe what each column holds, and the definitions sheet and build script then record how the entry sheet became a tidy analysis file.
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 source files, a variable list and a draft plan, 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
Describe the Rows
Before the Models
A file shaped to its design and a plan fixed before the output is seen leave far fewer decisions to defend later, whichever program the analysis then runs in.
No Commitment Required
Strictly Confidential
Fixed Project Fee
In-House PhD-Level Statisticians
Same-Day Response
Serving Researchers Since 2014