Contraceptive use is viewed as a safe and affordable way to halt rapid population growth and reduce maternal and infant mortality. Its use in Kenya remains a challenge despite the existence of family planning programmes initiated by the government and other stakeholders aimed at reducing fertility rate and increasing contraceptive use. This study aimed at modeling contraceptive use in Kenya among women of reproductive age using Multinomial logistic regression technique. A household based cross-sectional study was conducted between November 2008 and March 2009 by Kenya National Bureau of Statistics on women of reproductive age to determine the country’s Contraceptive Prevalence Rate and Total Fertility Rate among other indicators, whose results informed my data source. Multinomial logistic regression analysis was done in R version 3.2.1. statistical package. Modern method was the most preferred contraceptive method, of which Injectable, female sterilization and pills were the common types. Descriptive Analysis showed richest women aged between 30-34 years used modern contraceptives, while poorer women aged 35-39 years preferred traditional method. Multinomial Logistic Regression Analysis found marital status, Wealth category, Education level, place of Residence and the number of children a woman had as significant factors while age, religion and access to a health facility were insignificant. Simulation study showed that MLR parameters estimates converged to their true values while their standard errors reduced as sample size increased. Kolmogorov-Smirnov statistic of the MLR parameter estimates decreased while the P-value increased as the sample size increased and remained statistically insignificant. Marital status, Wealth category, Education level, place of Residence and the number of children a woman had could determine the contraceptive method a woman would choose, while age, religion and access to a health facility had no influence on the decision of choosing folkloric, traditional or modern method of contraception. MLR parameter estimates are consistent and normally distributed.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 5, Issue 4) |
| DOI | 10.11648/j.ajtas.20160504.21 |
| Page(s) | 242-251 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Contraceptive Method, Reproductive Age, Multinomial Logistic Regression (MLR), Consistent, Normally Distributed
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APA Style
Anthony Makau, Anthony G. Waititu, Joseph K. Mung’atu. (2016). Multinomial Logistic Regression for Modeling Contraceptive Use Among Women of Reproductive Age in Kenya. American Journal of Theoretical and Applied Statistics, 5(4), 242-251. https://doi.org/10.11648/j.ajtas.20160504.21
ACS Style
Anthony Makau; Anthony G. Waititu; Joseph K. Mung’atu. Multinomial Logistic Regression for Modeling Contraceptive Use Among Women of Reproductive Age in Kenya. Am. J. Theor. Appl. Stat. 2016, 5(4), 242-251. doi: 10.11648/j.ajtas.20160504.21
AMA Style
Anthony Makau, Anthony G. Waititu, Joseph K. Mung’atu. Multinomial Logistic Regression for Modeling Contraceptive Use Among Women of Reproductive Age in Kenya. Am J Theor Appl Stat. 2016;5(4):242-251. doi: 10.11648/j.ajtas.20160504.21
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Download@article{10.11648/j.ajtas.20160504.21,
author = {Anthony Makau and Anthony G. Waititu and Joseph K. Mung’atu},
title = {Multinomial Logistic Regression for Modeling Contraceptive Use Among Women of Reproductive Age in Kenya},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {5},
number = {4},
pages = {242-251},
doi = {10.11648/j.ajtas.20160504.21},
url = {https://doi.org/10.11648/j.ajtas.20160504.21},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20160504.21},
abstract = {Contraceptive use is viewed as a safe and affordable way to halt rapid population growth and reduce maternal and infant mortality. Its use in Kenya remains a challenge despite the existence of family planning programmes initiated by the government and other stakeholders aimed at reducing fertility rate and increasing contraceptive use. This study aimed at modeling contraceptive use in Kenya among women of reproductive age using Multinomial logistic regression technique. A household based cross-sectional study was conducted between November 2008 and March 2009 by Kenya National Bureau of Statistics on women of reproductive age to determine the country’s Contraceptive Prevalence Rate and Total Fertility Rate among other indicators, whose results informed my data source. Multinomial logistic regression analysis was done in R version 3.2.1. statistical package. Modern method was the most preferred contraceptive method, of which Injectable, female sterilization and pills were the common types. Descriptive Analysis showed richest women aged between 30-34 years used modern contraceptives, while poorer women aged 35-39 years preferred traditional method. Multinomial Logistic Regression Analysis found marital status, Wealth category, Education level, place of Residence and the number of children a woman had as significant factors while age, religion and access to a health facility were insignificant. Simulation study showed that MLR parameters estimates converged to their true values while their standard errors reduced as sample size increased. Kolmogorov-Smirnov statistic of the MLR parameter estimates decreased while the P-value increased as the sample size increased and remained statistically insignificant. Marital status, Wealth category, Education level, place of Residence and the number of children a woman had could determine the contraceptive method a woman would choose, while age, religion and access to a health facility had no influence on the decision of choosing folkloric, traditional or modern method of contraception. MLR parameter estimates are consistent and normally distributed.},
year = {2016}
}
TY - JOUR T1 - Multinomial Logistic Regression for Modeling Contraceptive Use Among Women of Reproductive Age in Kenya AU - Anthony Makau AU - Anthony G. Waititu AU - Joseph K. Mung’atu Y1 - 2016/07/23 PY - 2016 N1 - https://doi.org/10.11648/j.ajtas.20160504.21 DO - 10.11648/j.ajtas.20160504.21 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 242 EP - 251 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20160504.21 AB - Contraceptive use is viewed as a safe and affordable way to halt rapid population growth and reduce maternal and infant mortality. Its use in Kenya remains a challenge despite the existence of family planning programmes initiated by the government and other stakeholders aimed at reducing fertility rate and increasing contraceptive use. This study aimed at modeling contraceptive use in Kenya among women of reproductive age using Multinomial logistic regression technique. A household based cross-sectional study was conducted between November 2008 and March 2009 by Kenya National Bureau of Statistics on women of reproductive age to determine the country’s Contraceptive Prevalence Rate and Total Fertility Rate among other indicators, whose results informed my data source. Multinomial logistic regression analysis was done in R version 3.2.1. statistical package. Modern method was the most preferred contraceptive method, of which Injectable, female sterilization and pills were the common types. Descriptive Analysis showed richest women aged between 30-34 years used modern contraceptives, while poorer women aged 35-39 years preferred traditional method. Multinomial Logistic Regression Analysis found marital status, Wealth category, Education level, place of Residence and the number of children a woman had as significant factors while age, religion and access to a health facility were insignificant. Simulation study showed that MLR parameters estimates converged to their true values while their standard errors reduced as sample size increased. Kolmogorov-Smirnov statistic of the MLR parameter estimates decreased while the P-value increased as the sample size increased and remained statistically insignificant. Marital status, Wealth category, Education level, place of Residence and the number of children a woman had could determine the contraceptive method a woman would choose, while age, religion and access to a health facility had no influence on the decision of choosing folkloric, traditional or modern method of contraception. MLR parameter estimates are consistent and normally distributed. VL - 5 IS - 4 ER -
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