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Showing 1 to 12 of 168 entries
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Asymptotics of nonparametric L-1 regression models with dependent data.

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability

Zhao Z, Wei Y, Lin DK.
PMID: 24955016
Bernoulli (Andover). 2014 Aug 01;20(3):1532-1559. doi: 10.3150/13-BEJ532.

We investigate asymptotic properties of least-absolute-deviation or median quantile estimates of the location and scale functions in nonparametric regression models with dependent data from multiple subjects. Under a general dependence structure that allows for longitudinal data and some spatially...

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Zhao Z, Wei Y, Lin DK. Asymptotics of nonparametric L-1 regression models with dependent data. Bernoulli (Andover). 2014;20(3):1532-1559doi: 10.3150/13-BEJ532.
Zhao, Z., Wei, Y., & Lin, D. K. (2014). Asymptotics of nonparametric L-1 regression models with dependent data. Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 20(3), 1532-1559. https://doi.org/10.3150/13-BEJ532
Zhao, Zhibiao, et al. "Asymptotics of nonparametric L-1 regression models with dependent data." Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability vol. 20,3 (2014): 1532-1559. doi: https://doi.org/10.3150/13-BEJ532
Zhao Z, Wei Y, Lin DK. Asymptotics of nonparametric L-1 regression models with dependent data. Bernoulli (Andover). 2014 Aug 01;20(3):1532-1559. doi: 10.3150/13-BEJ532. PMID: 24955016; PMCID: PMC4060752.
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"It felt good but weird at the same time": Emerging adults' first experiences of six different sexual behaviors.

Journal of adolescent research

Vasilenko SA, Maas MK, Lefkowitz ES.
PMID: 26366039
J Adolesc Res. 2015 Sep 01;30(5):586-606. doi: 10.1177/0743558414561298.

Although sexual behavior is multidimensional, little research has focused on the experience of non-intercourse behaviors for adolescents and emerging adults. This paper uses open-ended coded data from a longitudinal study of college students (

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Vasilenko SA, Maas MK, Lefkowitz ES. "It felt good but weird at the same time": Emerging adults' first experiences of six different sexual behaviors. J Adolesc Res. 2015;30(5):586-606doi: 10.1177/0743558414561298.
Vasilenko, S. A., Maas, M. K., & Lefkowitz, E. S. (2015). "It felt good but weird at the same time": Emerging adults' first experiences of six different sexual behaviors. Journal of adolescent research, 30(5), 586-606. https://doi.org/10.1177/0743558414561298
Vasilenko, Sara A, et al. ""It felt good but weird at the same time": Emerging adults' first experiences of six different sexual behaviors." Journal of adolescent research vol. 30,5 (2015): 586-606. doi: https://doi.org/10.1177/0743558414561298
Vasilenko SA, Maas MK, Lefkowitz ES. "It felt good but weird at the same time": Emerging adults' first experiences of six different sexual behaviors. J Adolesc Res. 2015 Sep 01;30(5):586-606. doi: 10.1177/0743558414561298. PMID: 26366039; PMCID: PMC4562790.
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Partial linear varying multi-index coefficient model for integrative gene-environment interactions.

Statistica Sinica

Liu X, Cui Y, Li R.
PMID: 27667907
Stat Sin. 2016 Jul;26:1037-1060. doi: 10.5705/ss.202015.0114.

Gene-environment (G×E) interactions play key roles in many complex diseases. An increasing number of epidemiological studies have shown the combined effect of multiple environmental exposures on disease risk. However, no appropriate statistical models have been developed to conduct a...

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Liu X, Cui Y, Li R. Partial linear varying multi-index coefficient model for integrative gene-environment interactions. Stat Sin. 2016;26:1037-1060doi: 10.5705/ss.202015.0114.
Liu, X., Cui, Y., & Li, R. (2016). Partial linear varying multi-index coefficient model for integrative gene-environment interactions. Statistica Sinica, 261037-1060. https://doi.org/10.5705/ss.202015.0114
Liu, Xu, et al. "Partial linear varying multi-index coefficient model for integrative gene-environment interactions." Statistica Sinica vol. 26 (2016): 1037-1060. doi: https://doi.org/10.5705/ss.202015.0114
Liu X, Cui Y, Li R. Partial linear varying multi-index coefficient model for integrative gene-environment interactions. Stat Sin. 2016 Jul;26:1037-1060. doi: 10.5705/ss.202015.0114. PMID: 27667907; PMCID: PMC5033130.
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Quasi-Experimental Study of Functional Family Therapy Effectiveness for Juvenile Justice Aftercare in a Racially and Ethnically Diverse Community Sample.

Children and youth services review

Darnell AJ, Schuler MS.
PMID: 25767310
Child Youth Serv Rev. 2015 Mar;50:75-82. doi: 10.1016/j.childyouth.2015.01.013.

Functional Family Therapy (FFT) is an intensive community-based treatment program designed to reduce youth behavior problems such as violence, drug use, and other delinquency. Although there is evidence of FFT efficacy and effectiveness with predominantly White samples, there is...

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Darnell AJ, Schuler MS. Quasi-Experimental Study of Functional Family Therapy Effectiveness for Juvenile Justice Aftercare in a Racially and Ethnically Diverse Community Sample. Child Youth Serv Rev. 2015;50:75-82doi: 10.1016/j.childyouth.2015.01.013.
Darnell, A. J., & Schuler, M. S. (2015). Quasi-Experimental Study of Functional Family Therapy Effectiveness for Juvenile Justice Aftercare in a Racially and Ethnically Diverse Community Sample. Children and youth services review, 5075-82. https://doi.org/10.1016/j.childyouth.2015.01.013
Darnell, Adam J, and Schuler, Megan S. "Quasi-Experimental Study of Functional Family Therapy Effectiveness for Juvenile Justice Aftercare in a Racially and Ethnically Diverse Community Sample." Children and youth services review vol. 50 (2015): 75-82. doi: https://doi.org/10.1016/j.childyouth.2015.01.013
Darnell AJ, Schuler MS. Quasi-Experimental Study of Functional Family Therapy Effectiveness for Juvenile Justice Aftercare in a Racially and Ethnically Diverse Community Sample. Child Youth Serv Rev. 2015 Mar;50:75-82. doi: 10.1016/j.childyouth.2015.01.013. PMID: 25767310; PMCID: PMC4354807.
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Personality Profiles and Frequent Heavy Drinking in Young Adulthood.

Personality and individual differences

Zhang J, Bray BC, Zhang M, Lanza ST.
PMID: 25892836
Pers Individ Dif. 2015 Jul 01;80:18-21. doi: 10.1016/j.paid.2015.01.054.

Few studies examining the link between personality and alcohol use have adopted a comprehensive modeling framework to take into account individuals' profiles across multiple personality traits. In this study, latent profile analysis (LPA) was applied to a national sample...

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Zhang J, Bray BC, Zhang M, et al. Personality Profiles and Frequent Heavy Drinking in Young Adulthood. Pers Individ Dif. 2015;80:18-21doi: 10.1016/j.paid.2015.01.054.
Zhang, J., Bray, B. C., Zhang, M., & Lanza, S. T. (2015). Personality Profiles and Frequent Heavy Drinking in Young Adulthood. Personality and individual differences, 8018-21. https://doi.org/10.1016/j.paid.2015.01.054
Zhang, Jieting, et al. "Personality Profiles and Frequent Heavy Drinking in Young Adulthood." Personality and individual differences vol. 80 (2015): 18-21. doi: https://doi.org/10.1016/j.paid.2015.01.054
Zhang J, Bray BC, Zhang M, Lanza ST. Personality Profiles and Frequent Heavy Drinking in Young Adulthood. Pers Individ Dif. 2015 Jul 01;80:18-21. doi: 10.1016/j.paid.2015.01.054. PMID: 25892836; PMCID: PMC4397499.
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Modeling Expression Plasticity of Genes that Differentiate Drug-sensitive from Drug-resistant Cells to Chemotherapeutic Treatment.

Current genomics

Wang N, Wang Y, Han H, Huber KJ, Yang JM, Li R, Wu R.
PMID: 25435798
Curr Genomics. 2014 Oct;15(5):349-56. doi: 10.2174/138920291505141106102854.

By measuring gene expression at an unprecedented resolution and throughput, RNA-seq has played a pivotal role in studying biological functions. Its typical application in clinical medicine is to identify the discrepancies of gene expression between two different types of...

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Wang N, Wang Y, Han H, et al. Modeling Expression Plasticity of Genes that Differentiate Drug-sensitive from Drug-resistant Cells to Chemotherapeutic Treatment. Curr Genomics. 2014;15(5):349-56doi: 10.2174/138920291505141106102854.
Wang, N., Wang, Y., Han, H., Huber, K. J., Yang, J. M., Li, R., & Wu, R. (2014). Modeling Expression Plasticity of Genes that Differentiate Drug-sensitive from Drug-resistant Cells to Chemotherapeutic Treatment. Current genomics, 15(5), 349-56. https://doi.org/10.2174/138920291505141106102854
Wang, Ningtao, et al. "Modeling Expression Plasticity of Genes that Differentiate Drug-sensitive from Drug-resistant Cells to Chemotherapeutic Treatment." Current genomics vol. 15,5 (2014): 349-56. doi: https://doi.org/10.2174/138920291505141106102854
Wang N, Wang Y, Han H, Huber KJ, Yang JM, Li R, Wu R. Modeling Expression Plasticity of Genes that Differentiate Drug-sensitive from Drug-resistant Cells to Chemotherapeutic Treatment. Curr Genomics. 2014 Oct;15(5):349-56. doi: 10.2174/138920291505141106102854. PMID: 25435798; PMCID: PMC4245695.
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Inference for local autocorrelations in locally stationary models.

Journal of business & economic statistics : a publication of the American Statistical Association

Zhao Z.
PMID: 26097285
J Bus Econ Stat. 2015 Apr 01;33(2):296-306. doi: 10.1080/07350015.2014.948177.

For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our constructed simultaneous confidence band can be used to address...

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Zhao Z. Inference for local autocorrelations in locally stationary models. J Bus Econ Stat. 2015;33(2):296-306doi: 10.1080/07350015.2014.948177.
Zhao, Z. (2015). Inference for local autocorrelations in locally stationary models. Journal of business & economic statistics : a publication of the American Statistical Association, 33(2), 296-306. https://doi.org/10.1080/07350015.2014.948177
Zhao, Zhibiao. "Inference for local autocorrelations in locally stationary models." Journal of business & economic statistics : a publication of the American Statistical Association vol. 33,2 (2015): 296-306. doi: https://doi.org/10.1080/07350015.2014.948177
Zhao Z. Inference for local autocorrelations in locally stationary models. J Bus Econ Stat. 2015 Apr 01;33(2):296-306. doi: 10.1080/07350015.2014.948177. PMID: 26097285; PMCID: PMC4469395.
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Changes in Religiosity After First Intercourse in the Transition to Adulthood.

Psychology of religion and spirituality

Vasilenko SA, Lefkowitz ES.
PMID: 25580182
Psycholog Relig Spiritual. 2014 Nov;6(4):310-315. doi: 10.1037/a0037472.

Religiosity delays initiation of sexual behavior, but the association may be bidirectional, and individuals may become less religious after first intercourse. This study uses longitudinal data from college students to examine whether two aspects of religiosity change before and...

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Vasilenko SA, Lefkowitz ES. Changes in Religiosity After First Intercourse in the Transition to Adulthood. Psycholog Relig Spiritual. 2014;6(4):310-315doi: 10.1037/a0037472.
Vasilenko, S. A., & Lefkowitz, E. S. (2014). Changes in Religiosity After First Intercourse in the Transition to Adulthood. Psychology of religion and spirituality, 6(4), 310-315. https://doi.org/10.1037/a0037472
Vasilenko, Sara A, and Lefkowitz, Eva S. "Changes in Religiosity After First Intercourse in the Transition to Adulthood." Psychology of religion and spirituality vol. 6,4 (2014): 310-315. doi: https://doi.org/10.1037/a0037472
Vasilenko SA, Lefkowitz ES. Changes in Religiosity After First Intercourse in the Transition to Adulthood. Psycholog Relig Spiritual. 2014 Nov;6(4):310-315. doi: 10.1037/a0037472. PMID: 25580182; PMCID: PMC4286182.
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Long-term consequences of early sexual initiation on young adult health: A causal inference approach.

The Journal of early adolescence

Kugler KC, Vasilenko SA, Butera NM, Coffman DL.
PMID: 28529400
J Early Adolesc. 2017 May;37(5):662-676. doi: 10.1177/0272431615620666. Epub 2015 Dec 09.

Although early sexual initiation has been linked to negative outcomes, it is unknown whether these effects are causal. In this study, we use propensity score methods to estimate the causal effect of early sexual initiation on young adult sexual...

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Kugler KC, Vasilenko SA, Butera NM, et al. Long-term consequences of early sexual initiation on young adult health: A causal inference approach. J Early Adolesc. 2015;37(5):662-676doi: 10.1177/0272431615620666.
Kugler, K. C., Vasilenko, S. A., Butera, N. M., & Coffman, D. L. (2017). Long-term consequences of early sexual initiation on young adult health: A causal inference approach. The Journal of early adolescence, 37(5), 662-676. https://doi.org/10.1177/0272431615620666
Kugler, Kari C, et al. "Long-term consequences of early sexual initiation on young adult health: A causal inference approach." The Journal of early adolescence vol. 37,5 (2017): 662-676. doi: https://doi.org/10.1177/0272431615620666
Kugler KC, Vasilenko SA, Butera NM, Coffman DL. Long-term consequences of early sexual initiation on young adult health: A causal inference approach. J Early Adolesc. 2017 May;37(5):662-676. doi: 10.1177/0272431615620666. Epub 2015 Dec 09. PMID: 28529400; PMCID: PMC5435379.
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Feature Screening in Ultrahigh Dimensional Cox's Model.

Statistica Sinica

Yang G, Yu Y, Li R, Buu A.
PMID: 27418749
Stat Sin. 2016;26:881-901. doi: 10.5705/ss.2014.171.

Survival data with ultrahigh dimensional covariates such as genetic markers have been collected in medical studies and other fields. In this work, we propose a feature screening procedure for the Cox model with ultrahigh dimensional covariates. The proposed procedure...

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Yang G, Yu Y, Li R, et al. Feature Screening in Ultrahigh Dimensional Cox's Model. Stat Sin. 2016;26:881-901doi: 10.5705/ss.2014.171.
Yang, G., Yu, Y., Li, R., & Buu, A. (2016). Feature Screening in Ultrahigh Dimensional Cox's Model. Statistica Sinica, 26881-901. https://doi.org/10.5705/ss.2014.171
Yang, Guangren, et al. "Feature Screening in Ultrahigh Dimensional Cox's Model." Statistica Sinica vol. 26 (2016): 881-901. doi: https://doi.org/10.5705/ss.2014.171
Yang G, Yu Y, Li R, Buu A. Feature Screening in Ultrahigh Dimensional Cox's Model. Stat Sin. 2016;26:881-901. doi: 10.5705/ss.2014.171. PMID: 27418749; PMCID: PMC4939909.
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ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME.

Health services & outcomes research methodology

Schuler MS, Leoutsakos JS, Stuart EA.
PMID: 25530706
Health Serv Outcomes Res Methodol. 2014 Dec;14(4):232-254. doi: 10.1007/s10742-014-0122-0.

Confounding is widely recognized in settings where all variables are fully observed, yet recognition of and statistical methods to address confounding in the context of latent class regression are slowly emerging. In this study we focus on confounding when...

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Schuler MS, Leoutsakos JS, Stuart EA. ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME. Health Serv Outcomes Res Methodol. 2014;14(4):232-254doi: 10.1007/s10742-014-0122-0.
Schuler, M. S., Leoutsakos, J. S., & Stuart, E. A. (2014). ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME. Health services & outcomes research methodology, 14(4), 232-254. https://doi.org/10.1007/s10742-014-0122-0
Schuler, Megan S, et al. "ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME." Health services & outcomes research methodology vol. 14,4 (2014): 232-254. doi: https://doi.org/10.1007/s10742-014-0122-0
Schuler MS, Leoutsakos JS, Stuart EA. ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME. Health Serv Outcomes Res Methodol. 2014 Dec;14(4):232-254. doi: 10.1007/s10742-014-0122-0. PMID: 25530706; PMCID: PMC4269287.
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Variable selection for multivariate failure time data.

Biometrika

Cai J, Fan J, Li R, Zhou H.
PMID: 19458784
Biometrika. 2005;92(2):303-316. doi: 10.1093/biomet/92.2.303.

In this paper, we proposed a penalised pseudo-partial likelihood method for variable selection with multivariate failure time data with a growing number of regression coefficients. Under certain regularity conditions, we show the consistency and asymptotic normality of the penalised...

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Cai J, Fan J, Li R, et al. Variable selection for multivariate failure time data. Biometrika. 2005;92(2):303-316doi: 10.1093/biomet/92.2.303.
Cai, J., Fan, J., Li, R., & Zhou, H. (2005). Variable selection for multivariate failure time data. Biometrika, 92(2), 303-316. https://doi.org/10.1093/biomet/92.2.303
Cai, Jianwen, et al. "Variable selection for multivariate failure time data." Biometrika vol. 92,2 (2005): 303-316. doi: https://doi.org/10.1093/biomet/92.2.303
Cai J, Fan J, Li R, Zhou H. Variable selection for multivariate failure time data. Biometrika. 2005;92(2):303-316. doi: 10.1093/biomet/92.2.303. PMID: 19458784; PMCID: PMC2674767.
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Showing 1 to 12 of 168 entries