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AcademicFix Studio 1.1.1 · Synthetic data check

Check an SPSS .sav file in Studio: labels, missing values and scope

Studio 1.1.1 can import a .sav file directly as a document; CSV conversion is not required first. Use the synthetic example below to check raw codes, the data dictionary and the document scope of one message.

Content checked: 16 October 2026 · AcademicFix Editorial Team

Start with four synthetic rows, not real research data

Open a new data file in IBM SPSS Statistics. In Variable View, define numeric case_id, group and score variables; add value labels 1 = Control and 2 = Practice for group, and declare 99 as a user-defined missing value for score. Enter only the invented rows below in Data View and save a .sav copy.

Invented teaching data only; these are not analysis results. On mobile, scroll right to see the remaining columns.
case_idgroupscoreExpected reading
1112Control; valid score
2199Control; 99 is a missing-value code
3215Practice; valid score
4218Practice; valid score

Record the row count, variable names and Variable View settings in the original .sav file; these are your reference for the next check. IBM: SPSS data files.

Add the .sav file directly as a document

  1. Open a project in Studio for this trial only. Use the Documents file picker or drop the .sav file onto the shared desk.
  2. Open the extracted data text and import notes from the document card. Compare the data table, variable/value labels and missing-value definitions with the original SPSS file.
  3. If import fails, check file size and data scope. In 1.1.1, the file limit is 50 MiB; the imported table limit is 25,000 rows and 500 columns, and extracted content is capped at 500,000 characters. Split a large or complex file before retrying.

Studio import extracts raw codes and data-dictionary fields; this step does not run a new statistical analysis. Documents and import section.

Run three concrete checks on the same file

  1. Scope: Are four rows and three variables visible in the extracted table? For larger files, do not assume the view is merely a sample; read the import note.
  2. Codes and labels: Can you see raw 1/2 codes in the group column and the Control/Practice value labels separately in the dictionary? Do not confuse labels with raw data.
  3. Missing value: For case_id 2, verify both the score = 99 cell and the dictionary rule marking 99 as user missing. Do not include the visible 99 as a valid measurement in a mean.

Message document-scope options.

CSV export is an optional second route

Converting .sav to CSV is not a prerequisite for Studio 1.1.1. If another tool only accepts CSV, create a CSV copy using File > Save As in SPSS. Keep the original .sav and data dictionary; the CSV table alone does not guarantee preservation of SPSS labels and missing-value definitions.

In SPSS SAVE TRANSLATE settings, check whether the export writes raw codes or label text, and how it handles user-defined missing values. Recheck decimal separators, field delimiters and text encoding in the receiving tool.

IBM sources: Saving in external formats · /CELLS · /MISSING.

Separate import, analysis and data sharing

Adding a file to a project does not itself start a model call. Content included in a message or task may be sent to the selected cloud model provider; requested web operations may also send data to the relevant services. Running local analysis code requires separate project permission.

The visible desktop pilot in Studio 1.1.1 does not control the SPSS interface. Importing a .sav file promises neither a three-minute workflow, an automatic APA table, a correct test choice nor scientific validity. Run analysis in an authorized tool with a defined method; the researcher must verify the sample, missing data, assumptions, output values and APA presentation.

Studio local-analysis limits · Studio data flow · Research-data privacy checklist.

Sources and version scope

Studio behavior was checked on 16 October 2026 against read-only import code from the installed 1.1.1 build and its user guide; SPSS menu and file-format statements were checked against IBM documentation. No personal data was processed, and no duration or APA output was measured with a synthetic file. Recheck limits in later Studio/SPSS versions.

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