KTH Matematik  

Matematisk Statistik

Tid: 22 oktober 2013 kl 10.15-11.00.

Seminarierummet 3418, Institutionen för matematik, KTH, Lindstedts väg 25, plan 4. Karta!

Föredragshållare: Ina Lundström

Titel: Finding Risk Factors for Long-Term Sickness Absence Using Classification Trees (Examensarbete - Master thesis)

Abstract In this thesis a model for predicting if someone has an over-risk for long-term sickness absence is developed. The model is a classification tree that classifies objects as having high or low risk for long-term sickness absence based on their answers on the HealthWatch form. The HealthWatch form is a questionnare about health consisting of eleven questions, such as "How do you feel right now?", "How did you sleep last night?", "How is your job satisfaction right now?" e.t.c.. As a measure on risk for long-term sickness absence, the Oldenburg Burnout Inventory and a scale for performance based self-esteem are used.

Separate models are made for men and for women. The model for women shows good enough performance on a test set for being acceptable as a general model and can be used for prediction. Some conclusions can also be drawn from the additional information given by the classification tree; workload and work atmosphere do not seem to contribute a lot to an increased risk for long-term sickness absence, while joy at work probably is one of the most important factors.

The model for men performs very poorly on a test set, and therefore it is not advisable to use it for prediction or to draw other conclusions from it.

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Sidansvarig: Filip Lindskog
Uppdaterad: 31/01-2013