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Assessment of Quality of Life for the survivors of chronic diseases is considered an important outcome for understating their well-beings and for implementation of best treatment options. Such assessments are usually taken by a number of items covering all dimensions of Quality of life relative to the disease. Generally the responses of collected items are at ordinal categorical scale representing Quality of Life or well-beings of survivors in ordinal fashion. These ordinal items, when combined, to get summary score, usually results non-normal data distribution. Ordinal regression models are…mehr

Produktbeschreibung
Assessment of Quality of Life for the survivors of chronic diseases is considered an important outcome for understating their well-beings and for implementation of best treatment options. Such assessments are usually taken by a number of items covering all dimensions of Quality of life relative to the disease. Generally the responses of collected items are at ordinal categorical scale representing Quality of Life or well-beings of survivors in ordinal fashion. These ordinal items, when combined, to get summary score, usually results non-normal data distribution. Ordinal regression models are appropriate in these situations. In this study, proportional odd models with logit link function were used to model the ordinal response variables with explanatory variable(s). The main objective of the study was to assess the well-beings (physical, social, psychological and spirituals) and Quality of Life of the females breast cancer survivors and to determine the factors effecting well-beings (physical, social, psychological and spirituals) and Quality of Life of Pakistani breast cancer survivors females.
Autorenporträt
I gained my M.Phil degree in the subject of Statistics from the College of Statistical & Actuarial Sciences, University of the Punjab, Lahore-Pakistan in 2009. From November, 2010 to at present I am working as a lecturer at Lahore College for Women University, Lahore-Pakistan. As a researcher my interest is in applied statistics and Bio-Statistics.