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Analyzing Survey Response Time and Response Rate for Colorectal Cancer Patients Using Logistic and Poisson Regression
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2023 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Analys av svarstid och svarsfrekvens för patienter med kolorektal cancer med hjälp av regression (Swedish)
Abstract [en]

Cancer is a highly prevalent disease worldwide, claiming hundreds of lives each year. In the field of cancer research, it is customary to conduct surveys in which patients are asked to self-report and assess their symptoms and overall health. In such research, it is essential for patients to respond promptly to questionnaires to avoid recall bias and for a representative patient sample to respond to avoid biased sampling. This report aims to investigate the factors that impact response rate and response time using logistic regression and Poisson regression. The study focuses on a dataset of patients with colorectal cancer, with the response rate of patients with pancreatic cancer serving as a reference. By analyzing variables such as gender, age, place of residence, and the method of survey notification, the conclusion is that patients over the age of 80 who received their survey login codes on paper are the least responsive and underrepresented subgroup of the sample. In the analysis of the response time using Poisson regression, the conclusion is that the notification channel has the most significant impact on response rate.

Abstract [sv]

Cancer är en mycket utbredd sjukdom världen över och kräver hundratals liv varje år. Inom cancerforskningen är det vanligt att genomföra undersökningar där patienter ombeds att självrapportera och bedöma sina symtom och övergripande hälsa. I sådana undersökningar är det avgörande att patienterna svarar snabbt på enkäter för att undvika minnesbias och för att få fram en representativ patientgrupp och undvika snedvriden urvalsprocess. Syftet med denna rapport är att undersöka faktorer som påverkar svarsfrekvensen och svarstiden genom att använda logistisk regression och Poisson-regression. Studien fokuserar på en dataset av patienter med tjocktarmscancer, där svarsfrekvensen hos patienter med bukspottkörtelcancer används som referens. Genom att analysera variabler som kön, ålder, bostadsort och metod för undersökningsmeddelande dras slutsatsen att patienter över 80 år som fick sina inloggningskoder på papper är den minst responsiva och mest underrepresenterade undergruppen av urvalet. I analysen av svarstiden med hjälp av Poisson-regression dras slutsatsen att undersökningskanalen har den största påverkan på svarsfrekvensen.

Place, publisher, year, edition, pages
2023.
Series
TRITA-SCI-GRU ; 2023:230
Keywords [en]
Applied Mathematics, Regression, Poisson Regression, Logistic Regression, Statistics, Cancer, Patients, Healthcare
Keywords [sv]
Tillämpad Matematik, Statistik, Regression, Logistisk Regression, Poisson Regression, Cancer, Patientvård
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-342309OAI: oai:DiVA.org:kth-342309DiVA, id: diva2:1827750
External cooperation
Regionalt Cancercentrum (RCC)
Subject / course
Applied Mathematics and Industrial Economics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2024-01-15 Created: 2024-01-15 Last updated: 2024-01-15Bibliographically approved

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CiteExportLink to record
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