| Year |
Citation |
Score |
| 2022 |
Alexander M, Alkema L. A Bayesian Cohort Component Projection Model to Estimate Women of Reproductive Age at the Subnational Level in Data-Sparse Settings. Demography. 59: 1713-1737. PMID 36083610 DOI: 10.1215/00703370-10216406 |
0.448 |
|
| 2022 |
Bearak JM, Popinchalk A, Beavin C, Ganatra B, Moller AB, Tunçalp Ö, Alkema L. Country-specific estimates of unintended pregnancy and abortion incidence: a global comparative analysis of levels in 2015-2019. Bmj Global Health. 7. PMID 35332057 DOI: 10.1136/bmjgh-2021-007151 |
0.349 |
|
| 2022 |
Peterson E, Chou D, Moller AB, Gemmill A, Say L, Alkema L. Estimating misclassification errors in the reporting of maternal mortality in national civil registration vital statistics systems: A Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity for multiple countries and years with missing data. Statistics in Medicine. PMID 35165916 DOI: 10.1002/sim.9335 |
0.36 |
|
| 2022 |
Sharrow D, Hug L, You D, Alkema L, Black R, Cousens S, Croft T, Gaigbe-Togbe V, Gerland P, Guillot M, Hill K, Masquelier B, Mathers C, Pedersen J, Strong KL, et al. Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. The Lancet. Global Health. 10: e195-e206. PMID 35063111 DOI: 10.1016/S2214-109X(21)00515-5 |
0.367 |
|
| 2021 |
Cahill N, Sonneveldt E, Emmart P, Williamson J, Mbu R, Fodjo Yetgang AB, Dambula I, Azambuja G, Mahumane Govo AA, Joshi B, Felix S, Makashaka C, Ndaruhutse V, Serucaca J, Madzima B, ... ... Alkema L, et al. Using family planning service statistics to inform model-based estimates of modern contraceptive prevalence. Plos One. 16: e0258304. PMID 34714856 DOI: 10.1371/journal.pone.0258304 |
0.393 |
|
| 2021 |
Hug L, You D, Blencowe H, Mishra A, Wang Z, Fix MJ, Wakefield J, Moran AC, Gaigbe-Togbe V, Suzuki E, Blau DM, Cousens S, Creanga A, Croft T, Hill K, ... ... Alkema L, et al. Global, regional, and national estimates and trends in stillbirths from 2000 to 2019: a systematic assessment. Lancet (London, England). 398: 772-785. PMID 34454675 DOI: 10.1016/S0140-6736(21)01112-0 |
0.31 |
|
| 2021 |
Guranich G, Cahill N, Alkema L. : Estimating family planning indicators in R for a single population of interest. Gates Open Research. 5: 24. PMID 33842844 DOI: 10.12688/gatesopenres.13211.1 |
0.391 |
|
| 2020 |
Bearak J, Popinchalk A, Ganatra B, Moller AB, Tunçalp Ö, Beavin C, Kwok L, Alkema L. Unintended pregnancy and abortion by income, region, and the legal status of abortion: estimates from a comprehensive model for 1990-2019. The Lancet. Global Health. PMID 32710833 DOI: 10.1016/S2214-109X(20)30315-6 |
0.417 |
|
| 2019 |
Hug L, Alexander M, You D, Alkema L. National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis. The Lancet. Global Health. 7: e710-e720. PMID 31097275 DOI: 10.1016/S2214-109X(19)30163-9 |
0.401 |
|
| 2019 |
Chao F, Gerland P, Cook AR, Alkema L. Systematic assessment of the sex ratio at birth for all countries and estimation of national imbalances and regional reference levels. Proceedings of the National Academy of Sciences of the United States of America. PMID 30988199 DOI: 10.1073/Pnas.1812593116 |
0.468 |
|
| 2019 |
Bearak JM, Popinchalk A, Sedgh G, Ganatra B, Moller AB, Tunçalp Ö, Alkema L. Pregnancies, abortions, and pregnancy intentions: a protocol for modeling and reporting global, regional and country estimates. Reproductive Health. 16: 36. PMID 30894174 DOI: 10.1186/S12978-019-0682-0 |
0.396 |
|
| 2018 |
Masquelier B, Hug L, Sharrow D, You D, Hogan D, Hill K, Liu J, Pedersen J, Alkema L. Global, regional, and national mortality trends in older children and young adolescents (5-14 years) from 1990 to 2016: an analysis of empirical data. The Lancet. Global Health. 6: e1087-e1099. PMID 30223984 DOI: 10.1016/S2214-109X(18)30353-X |
0.327 |
|
| 2018 |
Chao F, You D, Pedersen J, Hug L, Alkema L. National and regional under-5 mortality rate by economic status for low-income and middle-income countries: a systematic assessment. The Lancet. Global Health. 6: e535-e547. PMID 29653627 DOI: 10.1016/S2214-109X(18)30059-7 |
0.417 |
|
| 2018 |
Bearak J, Popinchalk A, Alkema L, Sedgh G. Global, regional, and subregional trends in unintended pregnancy and its outcomes from 1990 to 2014: estimates from a Bayesian hierarchical model. The Lancet. Global Health. 6: e380-e389. PMID 29519649 DOI: 10.1016/S2214-109X(18)30029-9 |
0.385 |
|
| 2018 |
Alexander M, Alkema L. Global estimation of neonatal mortality using a Bayesian hierarchical splines regression model Demographic Research. 38: 335-372. DOI: 10.4054/Demres.2018.38.15 |
0.449 |
|
| 2017 |
Cahill N, Sonneveldt E, Stover J, Weinberger M, Williamson J, Wei C, Brown W, Alkema L. Modern contraceptive use, unmet need, and demand satisfied among women of reproductive age who are married or in a union in the focus countries of the Family Planning 2020 initiative: a systematic analysis using the Family Planning Estimation Tool. Lancet (London, England). PMID 29217374 DOI: 10.1016/S0140-6736(17)33104-5 |
0.338 |
|
| 2017 |
Ganatra B, Gerdts C, Rossier C, Johnson BR, Tunçalp Ö, Assifi A, Sedgh G, Singh S, Bankole A, Popinchalk A, Bearak J, Kang Z, Alkema L. Global, regional, and subregional classification of abortions by safety, 2010-14: estimates from a Bayesian hierarchical model. Lancet (London, England). PMID 28964589 DOI: 10.1016/S0140-6736(17)31794-4 |
0.391 |
|
| 2017 |
Kantorová V, New JR, Biddlecom A, Alkema L. Setting Ambitious yet Achievable Targets Using Probabilistic Projections: Meeting Demand for Family Planning. Studies in Family Planning. PMID 28518405 DOI: 10.1111/Sifp.12025 |
0.389 |
|
| 2017 |
Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, Grove JT, Hogan DR, Hogan MC, Horton R, Lawn JE, Marušic A, Mathers CD, Murray CJ, Rudan I, et al. [Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER Statement]. Epidemiologia E Servicos De Saude : Revista Do Sistema Unico De Saude Do Brasil. 26: 215-222. PMID 28226024 DOI: 10.5123/S1679-49742017000100023 |
0.387 |
|
| 2017 |
New JR, Cahill N, Stover J, Gupta YP, Alkema L. Levels and trends in contraceptive prevalence, unmet need, and demand for family planning for 29 states and union territories in India: a modelling study using the Family Planning Estimation Tool. The Lancet. Global Health. 5: e350-e358. PMID 28193400 DOI: 10.1016/S2214-109X(17)30033-5 |
0.385 |
|
| 2017 |
Alkema L, Zhang S, Chou D, Gemmill A, Moller A, Fat DM, Say L, Mathers C, Hogan D. A Bayesian approach to the global estimation of maternal mortality The Annals of Applied Statistics. 11: 1245-1274. DOI: 10.1214/16-Aoas1014 |
0.433 |
|
| 2016 |
Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, Grove JT, Hogan DR, Hogan MC, Horton R, Lawn JE, Marušić A, Mathers CD, Murray CJ, Rudan I, et al. Correction: Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. Plos Medicine. 13: e1002116. PMID 27504831 DOI: 10.1371/Journal.Pmed.1002116 |
0.331 |
|
| 2016 |
Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, Grove JT, Hogan DR, Hogan MC, Horton R, Lawn JE, Marušić A, Mathers CD, Murray CJ, Rudan I, et al. Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. Lancet (London, England). PMID 27371184 DOI: 10.1016/S0140-6736(16)30388-9 |
0.386 |
|
| 2016 |
Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, Grove JT, Hogan DR, Hogan MC, Horton R, Lawn JE, Marušić A, Mathers CD, Murray CJ, Rudan I, et al. Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. Plos Medicine. 13: e1002056. PMID 27351744 DOI: 10.1371/Journal.Pmed.1002056 |
0.374 |
|
| 2016 |
Sedgh G, Bearak J, Singh S, Bankole A, Popinchalk A, Ganatra B, Rossier C, Gerdts C, Tunçalp Ö, Johnson BR, Johnston HB, Alkema L. Abortion incidence between 1990 and 2014: global, regional, and subregional levels and trends. Lancet (London, England). PMID 27179755 DOI: 10.1016/S0140-6736(16)30380-4 |
0.386 |
|
| 2015 |
Alkema L, Gerland P, Raftery A, Wilmoth J. The United Nations Probabilistic Population Projections: An Introduction to Demographic Forecasting with Uncertainty. Foresight (Colchester, Vt.). 2015: 19-24. PMID 26617476 |
0.574 |
|
| 2015 |
Alkema L, Chou D, Hogan D, Zhang S, Moller AB, Gemmill A, Fat DM, Boerma T, Temmerman M, Mathers C, Say L. Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group. Lancet (London, England). PMID 26584737 DOI: 10.1097/01.Aoa.0000504718.91214.7D |
0.491 |
|
| 2015 |
You D, Hug L, Ejdemyr S, Idele P, Hogan D, Mathers C, Gerland P, New JR, Alkema L. Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. Lancet (London, England). PMID 26361942 DOI: 10.1016/S0140-6736(15)00120-8 |
0.488 |
|
| 2014 |
Phan TP, Alkema L, Tai ES, Tan KH, Yang Q, Lim WY, Teo YY, Cheng CY, Wang X, Wong TY, Chia KS, Cook AR. Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore. Bmj Open Diabetes Research & Care. 2: e000012. PMID 25452860 DOI: 10.1136/Bmjdrc-2013-000012 |
0.309 |
|
| 2014 |
Raftery AE, Alkema L, Gerland P. Bayesian Population Projections for the United Nations. Statistical Science : a Review Journal of the Institute of Mathematical Statistics. 29: 58-68. PMID 25324591 DOI: 10.1214/13-Sts419 |
0.609 |
|
| 2014 |
Alkema L, Chao F, You D, Pedersen J, Sawyer CC. National, regional, and global sex ratios of infant, child, and under-5 mortality and identification of countries with outlying ratios: a systematic assessment. The Lancet. Global Health. 2: e521-30. PMID 25304419 DOI: 10.1016/S2214-109X(14)70280-3 |
0.369 |
|
| 2014 |
Gerland P, Raftery AE, Sevčíková H, Li N, Gu D, Spoorenberg T, Alkema L, Fosdick BK, Chunn J, Lalic N, Bay G, Buettner T, Heilig GK, Wilmoth J. World population stabilization unlikely this century. Science (New York, N.Y.). 346: 234-7. PMID 25301627 DOI: 10.1126/Science.1257469 |
0.562 |
|
| 2014 |
Say L, Chou D, Gemmill A, Tunçalp Ö, Moller AB, Daniels J, Gülmezoglu AM, Temmerman M, Alkema L. Global causes of maternal death: a WHO systematic analysis. The Lancet. Global Health. 2: e323-33. PMID 25103301 DOI: 10.1016/S2214-109X(14)70227-X |
0.377 |
|
| 2014 |
Alkema L, New JR, Pedersen J, You D. Child mortality estimation 2013: an overview of updates in estimation methods by the United Nations Inter-agency Group for Child Mortality Estimation. Plos One. 9: e101112. PMID 25013954 DOI: 10.1371/Journal.Pone.0101112 |
0.471 |
|
| 2014 |
Alkema L, New JR. Global estimation of child mortality using a Bayesian B-spline bias-reduction model Annals of Applied Statistics. 8: 2122-2149. DOI: 10.1214/14-Aoas768 |
0.512 |
|
| 2013 |
Alkema L, Kantorova V, Menozzi C, Biddlecom A. National, regional, and global rates and trends in contraceptive prevalence and unmet need for family planning between 1990 and 2015: a systematic and comprehensive analysis. Lancet (London, England). 381: 1642-52. PMID 23489750 DOI: 10.1016/S0140-6736(12)62204-1 |
0.393 |
|
| 2013 |
Chao F, Alkema L. How Informative are Vital Registration Data for Estimating Maternal Mortality? A Bayesian Analysis of WHO Adjustment Data and Parameters Statistics and Public Policy. 1: 6-18. DOI: 10.1080/2330443X.2013.856148 |
0.312 |
|
| 2013 |
Alkema L, Jones GW, Lai CUR. Levels of urbanization in the world's countries: Testing consistency of estimates based on national definitions Journal of Population Research. 30: 291-304. DOI: 10.1007/S12546-013-9109-X |
0.451 |
|
| 2012 |
Alkema L, Raftery AE, Gerland P, Clark SJ, Pelletier F. Estimating trends in the total fertility rate with uncertainty using imperfect data: Examples from West Africa. Demographic Research. 26. PMID 24273449 DOI: 10.4054/Demres.2012.26.15 |
0.609 |
|
| 2012 |
Alkema L, New JR. Progress toward global reduction in under-five mortality: a bootstrap analysis of uncertainty in Millennium Development Goal 4 estimates. Plos Medicine. 9: e1001355. PMID 23239945 DOI: 10.1371/Journal.Pmed.1001355 |
0.48 |
|
| 2012 |
Alkema L, You D. Child mortality estimation: a comparison of UN IGME and IHME estimates of levels and trends in under-five mortality rates and deaths. Plos Medicine. 9: e1001288. PMID 22952434 DOI: 10.1371/Journal.Pmed.1001288 |
0.492 |
|
| 2012 |
Alkema L, Wong MB, Seah PR. Monitoring Progress Towards Millennium Development Goal 4: A Call for Improved Validation of Under-Five Mortality Rate Estimates Statistics, Politics, and Policy. 3. DOI: 10.1515/2151-7509.1043 |
0.34 |
|
| 2011 |
Ševčíková H, Alkema L, Raftery AE. bayesTFR: An R Package for Probabilistic Projections of the Total Fertility Rate. Journal of Statistical Software. 43: 1-29. PMID 27818617 DOI: 10.18637/Jss.V043.I01 |
0.605 |
|
| 2011 |
Alkema L, Ann WL. Estimating the under-five mortality rate using a bayesian hierarchical time series model. Plos One. 6: e23954. PMID 21969853 DOI: 10.1371/Journal.Pone.0023954 |
0.482 |
|
| 2011 |
Alkema L, Raftery AE, Gerland P, Clark SJ, Pelletier F, Buettner T, Heilig GK. Probabilistic projections of the total fertility rate for all countries. Demography. 48: 815-39. PMID 21748544 DOI: 10.1007/S13524-011-0040-5 |
0.631 |
|
| 2011 |
Ševčíková H, Alkema L, Raftery AE. bayesTFR: An R package for probabilistic projections of the total fertility rate Journal of Statistical Software. 43: 1-29. |
0.577 |
|
| 2010 |
Johnson LF, Alkema L, Dorrington RE. A Bayesian approach to uncertainty analysis of sexually transmitted infection models. Sexually Transmitted Infections. 86: 169-74. PMID 19880971 DOI: 10.1136/Sti.2009.037341 |
0.328 |
|
| 2008 |
Brown T, Salomon JA, Alkema L, Raftery AE, Gouws E. Progress and challenges in modelling country-level HIV/AIDS epidemics: the UNAIDS Estimation and Projection Package 2007. Sexually Transmitted Infections. 84: i5-i10. PMID 18647867 DOI: 10.1136/Sti.2008.030437 |
0.608 |
|
| 2008 |
Alkema L, Raftery AE, Brown T. Bayesian melding for estimating uncertainty in national HIV prevalence estimates. Sexually Transmitted Infections. 84: i11-i16. PMID 18647860 DOI: 10.1136/Sti.2008.029991 |
0.595 |
|
| 2007 |
Alkema L, Raftery AE, Clark SJ. Probabilistic projections of HIV prevalence using Bayesian melding The Annals of Applied Statistics. 1: 229-248. DOI: 10.1214/07-Aoas111 |
0.605 |
|
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