A marginal structural model for estimation of the effect of HIV positivity awareness on risky sexual behavior
暂无分享,去创建一个
[1] B. King. The Influence of Social Desirability on Sexual Behavior Surveys: A Review , 2022, Archives of Sexual Behavior.
[2] F. Dekker,et al. An introduction to inverse probability of treatment weighting in observational research , 2021, Clinical Kidney Journal.
[3] W. Groot,et al. Effects of HIV on gender gaps in school attendance of children in Zimbabwe: a non-linear multivariate decomposition analysis , 2021 .
[4] J. Mukherjee,et al. Assessing burden, risk factors, and perceived impact of uterine fibroids on women’s lives in rural Haiti: implications for advancing a health equity agenda, a mixed methods study , 2020, International Journal for Equity in Health.
[5] B. Maonga,et al. Determinants of Risky Sexual Behavioral Practices among Teen-girls in Malawi , 2020, The Open Public Health Journal.
[6] T. Berkessa,et al. High level risky sexual behavior among persons living with HIV in the urban setting of the highest HIV prevalent areas in Ethiopia: Implications for interventions , 2020, PloS one.
[7] J. Petkau,et al. Dealing with Treatment-confounder Feedback and Sparse Follow-up in Longitudinal studies - Application of a Marginal Structural Model in a Multiple Sclerosis Cohort. , 2020, American journal of epidemiology.
[8] J. Matovu,et al. Risk factors for HIV infection among married couples in Rakai, Uganda: a cross-sectional study , 2019, BMC Infectious Diseases.
[9] L. Sherr,et al. Screening and supporting through schools: educational experiences and needs of adolescents living with HIV in a South African cohort , 2019, BMC Public Health.
[10] K. Oppong Asante,et al. International note: Analysis of risk and protective factors for risky sexual behaviours among school-aged adolescents. , 2018, Journal of adolescence.
[11] J. Matovu,et al. Correlates of HIV status awareness among older adults in Uganda: results from a nationally representative survey , 2018, BMC Public Health.
[12] M. Tanner,et al. Linking gender, extramarital affairs, and HIV: a mixed methods study on contextual determinants of extramarital affairs in rural Tanzania , 2018, AIDS Research and Therapy.
[13] S. Blower,et al. Geographic variation in sexual behavior can explain geospatial heterogeneity in the severity of the HIV epidemic in Malawi , 2018, BMC Medicine.
[14] S. Vansteelandt,et al. Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods , 2017, American journal of epidemiology.
[15] Fabrice Carrat,et al. Performance of the marginal structural cox model for estimating individual and joined effects of treatments given in combination , 2017, BMC Medical Research Methodology.
[16] C. Kenyon,et al. Higher risk sexual behaviour is associated with unawareness of HIV-positivity and lack of viral suppression – implications for Treatment as Prevention , 2017, Scientific Reports.
[17] T. VanderWeele,et al. Causal inference and longitudinal data: a case study of religion and mental health , 2016, Social Psychiatry and Psychiatric Epidemiology.
[18] S. Kulkarni,et al. Educational outcomes of family-based HIV-infected and affected children from Maharashtra, India , 2016 .
[19] M. Glymour,et al. Using Marginal Structural Modeling to Estimate the Cumulative Impact of an Unconditional Tax Credit on Self-Rated Health. , 2016, American journal of epidemiology.
[20] J. Behrman,et al. Cohort Profile: The Malawi Longitudinal Study of Families and Health (MLSFH). , 2015, International journal of epidemiology.
[21] C. Eaton,et al. Effects of Glucosamine and Chondroitin Supplementation on Knee Osteoarthritis: An Analysis With Marginal Structural Models , 2015, Arthritis & rheumatology.
[22] K. Zuma,et al. Determinants of multiple sexual partnerships in South Africa. , 2015, Journal of public health.
[23] J. Behrman,et al. The Impact of Married Individuals Learning HIV Status in Malawi: Divorce, Number of Sexual Partners, and Condom Use With Spouses , 2015, Demography.
[24] J. Neal,et al. Awareness of HIV Status, Prevention Knowledge and Condom Use among People Living with HIV in Mozambique , 2014, PloS one.
[25] E. González-Jiménez,et al. Gender-based differences in the high-risk sexual behaviours of young people aged 15-29 in Melilla (Spain): a cross-sectional study , 2014, BMC Public Health.
[26] H. Kohler,et al. The Impact of AIDS Treatment on Savings and Human Capital Investment in Malawi , 2018 .
[27] S. Zuilkowski,et al. The impact of education on sexual behavior in sub-Saharan Africa: A review of the evidence , 2012, AIDS care.
[28] M. Petersen,et al. A marginal structural model to estimate the causal effect of antidepressant medication treatment on viral suppression among homeless and marginally housed persons with HIV. , 2010, Archives of general psychiatry.
[29] N. Madise,et al. HIV/AIDS and sexual-risk behaviors among adolescents: factors influencing the use of condoms in Burkina Faso. , 2007, African journal of reproductive health.
[30] S. Kalichman,et al. Recent multiple sexual partners and HIV transmission risks among people living with HIV/AIDS in Botswana , 2007, Sexually Transmitted Infections.
[31] J. Bartlett,et al. Highly active antiretroviral therapy and sexual risk behavior: A metaanalytic review , 2004 .
[32] J. Robins,et al. Effect of highly active antiretroviral therapy on time to acquired immunodeficiency syndrome or death using marginal structural models. , 2003, American journal of epidemiology.
[33] M. Carey,et al. Reliability of Retrospective Self-Reports of Sexual and Nonsexual Health Behaviors Among Women , 2002, Journal of sex & marital therapy.
[34] J. Robins,et al. Estimating the causal effect of zidovudine on CD4 count with a marginal structural model for repeated measures , 2002, Statistics in medicine.
[35] Anne M Johnson,et al. Measuring sexual behaviour: methodological challenges in survey research , 2001, Sexually transmitted infections.
[36] M. Pepe,et al. A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data , 1994 .