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Dataset

Tumor Growth

Abstract

This dataset contains repeated measurements of tumor size from an animal xenograft experiment designed to compare four treatments for cancers. Study animals were n=37 mice with baseline tumor volumes of between40-60 mm3. Animals were assigned to either: 1) control (n=8); drug only (n=10); 3) radiation only (n=10); or 4) drug + radiation (n=9). Tumor size was typically measured on work days for up to four weeks, but the number of repeated measurements is variable because some animals had to be euthanized.

Study DesignTopicStatistical MethodStatistical MethodStatistical Method
LongitudinalTumor GrowthLinear Mixed ModelsLongitudinal DataRepeated Measures

Contributor

The Tumor Growth dataset was contributed by Dr. Constantine Daskalakis, Associate Professor, Thomas Jefferson University. Please refer to this resource as: Constantine Daskalakis, “Tumor Growth Dataset”, TSHS Resources Portal (2016). Available at https://www.causeweb.org/tshs/tumor-growth/.

Background

When basic science research suggests a new possibility for cancer treatment, pre-clinical studies are performed to obtain preliminary assessment in vivo of the biological response of human tumors to that treatment. Such translational research often relies on tumor xenograft experiments in animal models.

Objective

The study’s two main specific aims were to assess whether: a) the drug has an effect on tumor growth; and b) the administration of the drug before radiation enhances the effect of the latter on tumor growth.

Subjects & Variables

Subject# Obs# VarIntroductionData Dictionary
Tumor Growth5744Tumor Growth-IntroductionTumor Growth-Data Dictionary

Data Downloads

Posting DateContributor (email)
07/19/16Constantine Daskalakis (constantine.daskalakis@jefferson.edu)
RSASSTATASPSSMinitabExcel
Tumor Growth-RTumor Growth-SASTumor Growth-StataTumor Growth-SPSSTumor Growth-MinitabTumor Growth-Excel

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Teaching Resources

last updated on 7/19/2016

#Name (link)Posting DateAuthor (email)TypeStatistical TopicLevelKeywords
1[restrict userlevel=”subscriber”]Resource 01[/restrict]7/19/2016Constantine Daskalakis (Constantine.Daskalakis@jefferson.edu)Lab/ProjectInferenceIntro/IntermediateMixed-Effects Modeling

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