Tumor Cell Cytokine Secretion Analysis with Linear Mixed-Effects Models

Linear mixed-effects model results analyzing the effects of tumor cell count and histology on cytokine secretion. The dataset contains statistical outputs from models with donor as a random intercept, including slopes for cell count effects and coefficient estimates for tumor type contrasts. It was authored by Rachel V. Brady and last updated on April 24, 2026.

Use Cases

• Replicate statistical analysis of cytokine secretion based on reported linear mixed-effects model parameters.
• Benchmark the effect of cell count on cytokine levels using the provided slope estimates.
• Compare cytokine secretion across different tumor histologies using the reported coefficient contrasts.
• Assess model fit diagnostics for similar experimental designs based on the described transformation and normality testing.

Strengths

• Model results are explicitly detailed, including slopes, intercepts, and F-statistics.
• Statistical methodology is clearly described, including log transformation and use of a random intercept for donors.
• Dataset is openly licensed under CC-BY-4.0.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 17.6 KB, indicating limited scope.

Provenance

Source

figshare, authored by Rachel V. Brady.

Collection Method

Analysis of experimental data using linear mixed-effects models.

Time Range

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Freshness

Last updated 2026-04-24 17:32:20; freshness should be verified.

Geography

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