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Dataset

Season Effect

Abstract

This data set contains 2,919 individual records of adults undergoing colorectal surgery. Age, gender, race, BMI, several risk factors, several surgical indices, vitamin D levels (on 5% of the patients, approx.), the key predictor (season) and the outcome (infection or not) are provided. The dataset is cleaned and complete (no missing data except for vitamin D levels). There are no outliers or data problems. These are data from a study by Turan et al,  “Season and vitamin D status do not affect probability for surgical site infection after colorectal surgery”, Turan et al., 2015, European Surgery; 47(6):341-5.

Study DesignTopicStatistical MethodStatistical MethodStatistical Method
Prospective CohortColorectal SurgeryContingency TablesLogistic Regression

Contributor

The Season Effect dataset was contributed by David Ngendahimana, Pre-Doctoral Fellow, Case-Western Reserve University. Please refer to this resource as: David Ngendahimana, “Season Effect Dataset”, TSHS Resources Portal (2016). Available at https://www.causeweb.org/tshs/season-effect/.

Background

Colorectal surgery is associated with a high rate of surgical site infection (SSI) and occurs in 11-28% of all patients who undergo this surgery.   Variations in SSI are hypothesized to be related to season and, in particular, season-related fluctuations in vitamin D.

Objective

This study aimed to compare rates of SSI among patients having colorectal surgery in winter to those having surgery in the summer.  Additional analyses compared rates of SSI among patients with high vitamin D concentration and those with low vitamin D concentration.

Subjects & Variables

Subject# Obs# VarIntroductionData Dictionary
Season Effect291914Season IntroductionSeason Data Dictionary

Data Downloads

Posting DateContributor (email)
07/14/16David Ngendahimana (dkn18@case.edu)
RSASSTATASPSSMinitabExcel
Season-RSeason-SASSeason-StataSeason-SPSSSeason-MinitabSeason-Excel

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Teaching Resources

last updated on 7/14/2016

#Name (link)Posting DateAuthor (email)TypeStatistical TopicLevelKeywords
1Resource 017/14/2016David Ngendahimana (dkn18@case.edu)HomeworkInferenceIntroductoryLogistic Regression

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