ANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN
This final project analyzes the relationship between oral health variables in normal and stunting children using the Hypothesis Testing, Correlation Matrix, Multiple Linear Regression, and Generalized Linear Model (GLM) approaches. The first step is to do an Exploratory Data Analysis (EDA) by lookin...
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id-itb.:752942023-07-26T13:46:31ZANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN Iqbal, Moh Indonesia Final Project stunting, GLM, logistic regression, link function, stepwise regression INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/75294 This final project analyzes the relationship between oral health variables in normal and stunting children using the Hypothesis Testing, Correlation Matrix, Multiple Linear Regression, and Generalized Linear Model (GLM) approaches. The first step is to do an Exploratory Data Analysis (EDA) by looking for descriptive statistics to get an initial idea of the processed data. Then do a hypothesis test to find which predictor variables are significant for normal and stunting children. The correlation matrix is used to see the relationship between the predictor variables whether there is collinearity or not. Finally, make modeling using GLM. The GLM model used is logistic regression with a logit link function with and without using the stepwise regression method to get the best model. It was found that the most significant oral health variable was the dental caries index (DMF) consisting of Decay (D), Missing (M), and Filling (F). text |
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This final project analyzes the relationship between oral health variables in normal and stunting children using the Hypothesis Testing, Correlation Matrix, Multiple Linear Regression, and Generalized Linear Model (GLM) approaches. The first step is to do an Exploratory Data Analysis (EDA) by looking for descriptive statistics to get an initial idea of the processed data. Then do a hypothesis test to find which predictor variables are significant for normal and stunting children. The correlation matrix is used to see the relationship between the predictor variables whether there is collinearity or not. Finally, make modeling using GLM. The GLM model used is logistic regression with a logit link function with and without using the stepwise regression method to get the best model. It was found that the most significant oral health variable was the dental caries index (DMF) consisting of Decay (D), Missing (M), and Filling (F). |
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Final Project |
author |
Iqbal, Moh |
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Iqbal, Moh ANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN |
author_facet |
Iqbal, Moh |
author_sort |
Iqbal, Moh |
title |
ANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN |
title_short |
ANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN |
title_full |
ANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN |
title_fullStr |
ANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN |
title_full_unstemmed |
ANALYSIS OF THE RELATIONSHIP BETWEEN ORAL HEALTH VARIABLES IN NORMAL AND STUNTING CHILDREN |
title_sort |
analysis of the relationship between oral health variables in normal and stunting children |
url |
https://digilib.itb.ac.id/gdl/view/75294 |
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1822280127265898496 |