Panel data analysis in medical research

Author(s):
Habib Ollah EsmariliHabib Ollah Esmarili, Moluk Hadi AlijanvandMoluk Hadi Alijanvand,*, Hasan DostiHasan Dosti, Mohamad taghi ShakeriMohamad taghi Shakeri
*Corresponding Author: Email: [email protected]

Koomesh:Vol. 14, issue 1; 39-46
Published online:Mar 25, 2012
Article type:Research Article
Received:Jan 03, 2011
Accepted:Apr 02, 2012
How to Cite:Esmarili HO, Hadi Alijanvand M, Dosti H, Shakeri MT. Panel data analysis in medical research. koomesh. 2012;14(1):e152547. doi:

Abstract

  Introduction: A longitudinal study involves repeated observations of the same items over long periods of time. Panel studies are longitudinal studies of batch which combine cross-sectional and time- series data in observations on a number of over time that play special role in medical research or clinical trials. In this paper, we primarily discuss about the panel data and various modeling of panel data. It is not possible to use ordinary regression methods due to inter- correlation of observation related to one unit. Generalized estimation equation (GEE) for estimation of panel regression coefficient by considering inter correlation was used among observations.   Materials and Methods: We considerd the importance of panel data modeling with GEE in real panel data samples as applications in the effect of estrogen patches on the postnatal depression .   Results: In the estimation of panel regression coefficients on real data, starting treatment effect (b(pre)=0.428, p

Copyright

© 2012, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.

Similar Articles

15
Aug
2006

A survey on missing values in osteoporosis using a weighted estimating equation

SeyedMojtaba Tabatabaei,
Hamid Alavi Majd,
Ali Akbar Khadem Maboudi

Tabatabaei S, Alavi Majd H, Khadem Maboudi AA. A survey on missing values in osteoporosis using a weighted estimating equation. koomesh. 2006;7(3):e153756. doi:

14
Nov
2015

Shedding Light on the Hidden Corners of Sampling

Bardia Panahbehagh

Panahbehagh B. Shedding Light on the Hidden Corners of Sampling. J Arch Mil Med. 2015;3(4):e29352. doi: https://doi.org/10.5812/jamm.29352

30
Sep
2010

Impact of Imputation of Missing Data on Estimation of Survival Rates: An Example in Breast Cancer

Mohammad Reza Baneshi,
AR Talei

Baneshi MR, Talei A. Impact of Imputation of Missing Data on Estimation of Survival Rates: An Example in Breast Cancer. Int J Cancer Manag. 2010;3(3):e80700. doi:

30
Mar
2015

Association of polymorphisms and other risk factors with cholesterol level over time using logic random effect model: Tehran Lipid and Glucose Study

Parvin Sarbakhsh,
Mehrabi Yadollah,
Maryam Daneshpour,
Farid Zayeri,
Mahshid Namdari

Sarbakhsh P, Yadollah M, Daneshpour M, Zayeri F, Namdari M. Association of polymorphisms and other risk factors with cholesterol level over time using logic random effect model: Tehran Lipid and Glucose Study. koomesh. 2024;16(2):e151298. doi:

28
Sep
2016

Time-dependent frailty model to gap times between recurrent events with application to epilepsy data

Samaneh Hossainzadeh,
Soghrat Faghihzadeh,
Mehdi Rahgozar,
Ebrahim Hajizadeh,
Seyed Sohrab Hashemi Fesharaki,
Marzieh Gharakhani

Hossainzadeh S, Faghihzadeh S, Rahgozar M, Hajizadeh E, Hashemi Fesharaki SS, et al. Time-dependent frailty model to gap times between recurrent events with application to epilepsy data. koomesh. 2016;17(3):e151227. doi:

Download PDF270.61 KB
Share on
Cited by
Metrics

Ordering Reprints

Articles are published under the Creative Commons license stated on each article. No permission or royalty fee is required for uses permitted by that license. CCC handles optional bulk and customized reprint orders. Any quotation covers production and delivery services only, not copyright permission. > Request Reprints from CCC 

Search Relations

Author(s):

Related Articles