- Library Home /
- Search Collections /
- Open Collections /
- Browse Collections /
- UBC Theses and Dissertations /
- Identification of risk groups : study of infant mortality...
Open Collections
UBC Theses and Dissertations
UBC Theses and Dissertations
Identification of risk groups : study of infant mortality in Sri Lanka Kan, Lisa
Abstract
Multivariate statistical methods, including recent computing-intensive techniques, are explained and applied in a medical sociology context to study infant death in relation to socioeconomic risk factors of households in Sri Lankan villages. The data analyzed were collected by a team of social scientists who interviewed households in Sri Lanka during 1980-81. Researchers would like to identify characteristics (risk factors) distinguishing those households at relatively high or low risk of experiencing an infant death. Furthermore, they would like to model temporal and structural relationships among important risk factors. Similar statistical issues and analyses are relevant to many sociological and epidemiological studies. Results from such studies may be useful to health promotion or preventive medicine program planning. With respect to an outcome such as infant death, risk groups and discriminating factors or variables can be identified using a variety of statistical discriminant methods, including Fisher's parametric (normal) linear discriminant, logistic linear discrimination, and recursive partitioning (CART). The usefulness of a particular discriminant methodology may depend on distributional properties of the data (whether the variables are dichotomous, ordinal, normal, etc.,) and also on the context and objectives of the analysis. There are at least three conceptual approaches to statistical studies of risk factors. An epidemiological perspective uses the notion of relative risk. A second approach, generally referred to as classification or discriminant analysis, is to predict a dichotomous outcome, or class membership. A third approach is to estimate the probability of each outcome, or of belonging to each class. These three approaches are discussed and compared; and appropriate methods are applied to the Sri Lankan household data. Path analysis is a standard method used to investigate causal relationships among variables in the social sciences. However, the normal multiple regression assumptions under which this method is developed are very restrictive. In this thesis, limitations of path analysis are explored, and alternative loglinear techniques are considered.
Item Metadata
Title |
Identification of risk groups : study of infant mortality in Sri Lanka
|
Creator | |
Publisher |
University of British Columbia
|
Date Issued |
1988
|
Description |
Multivariate statistical methods, including recent computing-intensive techniques, are explained and applied in a medical sociology context to study infant death in relation to socioeconomic risk factors of households in Sri Lankan villages.
The data analyzed were collected by a team of social scientists who interviewed households in Sri Lanka during 1980-81. Researchers would like to identify characteristics (risk factors) distinguishing those households at relatively high or low risk of experiencing an infant death. Furthermore, they would like to model temporal and structural relationships among important risk factors.
Similar statistical issues and analyses are relevant to many sociological and epidemiological studies. Results from such studies may be useful to health promotion or preventive medicine program planning.
With respect to an outcome such as infant death, risk groups and discriminating factors or variables can be identified using a variety of statistical discriminant methods, including Fisher's parametric (normal) linear discriminant, logistic linear discrimination, and recursive partitioning (CART). The usefulness of a particular discriminant methodology may depend on distributional properties of the data (whether the variables are dichotomous, ordinal, normal, etc.,) and also on the context and objectives of the analysis. There are at least three conceptual approaches to statistical studies of risk factors. An epidemiological perspective uses the notion of relative risk. A second approach, generally referred to as classification or discriminant analysis, is to predict a dichotomous outcome, or class membership. A third approach is to estimate the probability of each outcome, or of belonging to each class. These three approaches are discussed and compared; and appropriate methods are applied to the Sri Lankan household data.
Path analysis is a standard method used to investigate causal relationships among variables in the social sciences. However, the normal multiple regression assumptions under which this method is developed are very restrictive. In this thesis, limitations of path analysis are explored, and alternative loglinear techniques are considered.
|
Genre | |
Type | |
Language |
eng
|
Date Available |
2010-08-30
|
Provider |
Vancouver : University of British Columbia Library
|
Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
|
DOI |
10.14288/1.0097696
|
URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
|
Campus | |
Scholarly Level |
Graduate
|
Aggregated Source Repository |
DSpace
|
Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.