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Nath, Dilip C.
- An Application of Linear Mixed Effect Model to Compare the Drug Treatment Effect in Patients with Type 2 Diabetes
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Authors
Affiliations
1 Dept. of Statistics, Gauhati University
1 Dept. of Statistics, Gauhati University
Source
Indian Journal of Public Health Research & Development, Vol 4, No 1 (2013), Pagination: 24-27Abstract
In this article, different types of mixed effect models have been applied for drug effect comparison in type 2 diabetes patients. The mixed effect models have been applied through Bayesian approach and compared with frequency approach. The combination of metformin with pioglitazone is found to be effective compared to pioglitazone with gliclazide.Keywords
MCMC, FBS, AR(1)References
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- Regional Models Assessing Region-Specific Determinants of Low Birth Weight in India
Abstract Views :224 |
PDF Views:76
Authors
Affiliations
1 Symbiosis Institute of Health Sciences, Symbiosis International (Deemed) University, Pune 411 004, IN
2 Assam University, Silchar 788 011, IN
1 Symbiosis Institute of Health Sciences, Symbiosis International (Deemed) University, Pune 411 004, IN
2 Assam University, Silchar 788 011, IN
Source
Current Science, Vol 116, No 10 (2019), Pagination: 1674-1682Abstract
Low birth weight (LBW) is defined as birth weight less than 2.5 kg. LBW infants remain at a relatively higher risk of mortality than those with normal birth weight. This is still a major public health problem in developing countries like India. Data from the third round of the National Family Health Survey were used for this study. The multivariable logistic regression model demonstrated a significant association between the reporting of birth weight, and education level and financial status. Furthermore, as the rate of parity increased, the odds for reporting of birth weights decreased in the northern, central and eastern regions of India.Keywords
Heaping, Low Birth Weight, Regression Models, Region-Specific Determinants.References
- Channon, A. A., Padmadas, S. S. and McDonald, J. W., Measuring birth weight in developing countries: does the method of reporting in retrospective surveys matter? Matern. Child Health J., 2011, 15(1), 12-8.
- Blanc, A. K. et al., Monitoring low birth weight: an evaluation of international estimates and an updated estimation procedure. Bull. WHO, 2005, 83, 178–185.
- Gagan, A. et al., Maternal risk factors associated with low birth weight neonates in a tertiary care hospital, Northern India. J. Community Med. Health Educ., 2012, 2, 177.
- Kaushal, S. K. et al., A study of maternal factor and birth weight in a border district of Uttar Pradesh: a hospital based study. Indian J. Community Health, 2012, 24(2).
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- Dalal, A. et al., Epidemiological determinants of low birth weight in Ahmadabad city: a facility based case control study. Int. J. Med. Public Health, 2014, 3(4).
- Sahu, K. K. et al., Incidence of low birth weight and effect of maternal factors on birth weight of neonates in rural areas of Uttar Pradesh. Int. J. Multidiscip. Res. Develop., 2015, 2(3), 707–715.
- Noor, N., Kural, M., Joshi, T., Pandit, D. and Patil, A., Study of maternal determinants influencing birth weight of new born. Arch. Med. Health Sci., 2015, 3, 239–243.
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