The analysis of survival data is of considerable interest to studies in Division of Epidemiology, Statistics and Prevention Research and also to biomedical research in general as the data encountered is typically of that nature. Our objective in this project is multifold: (1) Develop methods to analyze time to an event which have non-standard type of incompleteness, that are beyond right censoring, like random truncation, current status and interval censoring. Extensive literature exists for dealing with data which are randomly right censored However, more effort is needed to develop methods to deal with other type of incompleteness which occur frequently. For example, random truncation is frequently observed in many retrospective pregnancy studies where women are enrolled in the study only if they have gotten pregnant by start of study. (2) Develop methods to deal with multivariate survival data. This part of the project is necessitated by needs of many epidemiological studies, where the interest is not just in modeling one simple event of interest, but rather a host of complex events. The focus of this part is to develop methods to analyze multivariate survival data like the multistage data, recurrent events and competing risks data. Examples of such multivariate data can be found in various studies being conducted in DESPR, NICHD like LIFE study and other prospective pregnancy studies, Safe Labor to name few. The methods developed here will address questions like modeling of progression of labot through various stages, modeling time to pregnancy to delivery or loss. Also, motivated by need to better understand the risk factors associated with women who suffer repeated adverse outcomes associated with pregnancy loss, we intend to study modeling such events using both the competing risks data as well as recurrent events data

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Liu, Danping; Yeung, Edwina H; McLain, Alexander C et al. (2017) A Two-Step Approach for Analysis of Nonignorable Missing Outcomes in Longitudinal Regression: an Application to Upstate KIDS Study. Paediatr Perinat Epidemiol 31:468-478
Sundaram, Rajeshwari; Ma, Ling; Ghoshal, Subhashis (2017) Median Analysis of Repeated Measures Associated with Recurrent Events in Presence of Terminal Event. Int J Biostat 13:
Ghassabian, Akhgar; Sundaram, Rajeshwari; Wylie, Amanda et al. (2016) Maternal medical conditions during pregnancy and gross motor development up to age 24 months in the Upstate KIDS study. Dev Med Child Neurol 58:728-34
Ghassabian, Akhgar; Sundaram, Rajeshwari; Bell, Erin et al. (2016) Gross Motor Milestones and Subsequent Development. Pediatrics 138:
Sapra, Katherine J; Barr, Dana B; Maisog, José M et al. (2016) Time-to-Pregnancy Associated With Couples' Use of Tobacco Products. Nicotine Tob Res 18:2154-2161
Lum, Kirsten J; Sundaram, Rajeshwari; Louis, Thomas A (2015) Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length. Biostatistics 16:113-28
Wylie, Amanda; Sundaram, Rajeshwari; Kus, Christopher et al. (2015) Maternal prepregnancy obesity and achievement of infant motor developmental milestones in the upstate KIDS study. Obesity (Silver Spring) 23:907-13
Katki, Hormuzd A; Cheung, Li C; Fetterman, Barbara et al. (2015) A joint model of persistent human papillomavirus infection and cervical cancer risk: Implications for cervical cancer screening. J R Stat Soc Ser A Stat Soc 178:903-923
McLain, Alexander C; Sundaram, Rajeshwari; Buck Louis, Germaine M (2015) Joint analysis of longitudinal and survival data measured on nested timescales by using shared parameter models: an application to fecundity data. J R Stat Soc Ser C Appl Stat 64:339-357
Sapra, Katherine J; McLain, Alexander C; Maisog, José M et al. (2015) Clustering of retrospectively reported and prospectively observed time-to-pregnancy. Ann Epidemiol 25:959-63

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