scholarly journals Humpback whales within the Brazilian breeding ground: distribution and population size estimate

2010 ◽  
Vol 11 (3) ◽  
pp. 233-243 ◽  
Author(s):  
A Andriolo ◽  
PG Kinas ◽  
MH Engel ◽  
CC Albuquerque Martins ◽  
AM Rufino
2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Isabel Sathane ◽  
Makini A.S. Boothe ◽  
Roberta Horth ◽  
Cynthia Semá Baltazar ◽  
Noela Chicuecue ◽  
...  

2005 ◽  
Vol 72 (2) ◽  
pp. 214-216 ◽  
Author(s):  
Kathrin Lüttmann ◽  
Nils Anthes ◽  
Thomas G. D'Souza ◽  
Simone Riss ◽  
Nico K. Michiels

2015 ◽  
Vol 31 (3) ◽  
pp. 357-379 ◽  
Author(s):  
Susanna C. Gerritse ◽  
Peter G.M. van der Heijden ◽  
Bart F.M. Bakker

Abstract An important quality aspect of censuses is the degree of coverage of the population. When administrative registers are available undercoverage can be estimated via capture-recapture methodology. The standard approach uses the log-linear model that relies on the assumption that being in the first register is independent of being in the second register. In models using covariates, this assumption of independence is relaxed into independence conditional on covariates. In this article we describe, in a general setting, how sensitivity analyses can be carried out to assess the robustness of the population size estimate. We make use of log-linear Poisson regression using an offset, to simulate departure from the model. This approach can be extended to the case where we have covariates observed in both registers, and to a model with covariates observed in only one register. The robustness of the population size estimate is a function of implied coverage: as implied coverage is low the robustness is low. We conclude that it is important for researchers to investigate and report the estimated robustness of their population size estimate for quality reasons. Extensions are made to log-linear modeling in case of more than two registers and the multiplier method


Copeia ◽  
1991 ◽  
Vol 1991 (4) ◽  
pp. 1139 ◽  
Author(s):  
Engkamat Ak. Lading ◽  
Robert B. Stuebing ◽  
Harold K. Voris

2012 ◽  
Vol 6 (1) ◽  
pp. 98-107 ◽  
Author(s):  
David W Purcell ◽  
Christopher H Johnson ◽  
Amy Lansky ◽  
Joseph Prejean ◽  
Renee Stein ◽  
...  

Background: CDC has not previously calculated disease rates for men who have sex with men (MSM) because there is no single comprehensive source of data on population size. To inform prevention planning, CDC developed a national population size estimate for MSM to calculate disease metrics for HIV and syphilis. Methods: We conducted a systematic literature search and identified seven surveys that provided data on same-sex behavior in nationally representative samples. Data were pooled by three recall periods and combined using meta-analytic procedures. We applied the proportion of men reporting same-sex behavior in the past 5 years to U.S. census data to produce a population size estimate. We then calculated three disease metrics using CDC HIV and STD surveillance data and rate ratios comparing MSM to other men and to women. Results: Estimates of the proportion of men who engaged in same-sex behavior differed by recall period: past year = 2.9% (95%CI, 2.6–3.2); past five years = 3.9% (3.5–4.4); ever = 6.9% (5.1–8.6). Rates on all 3 disease metrics were much higher among MSM than among either other men or women (38 to 109 times as high). Conclusions: Estimating the population size for MSM allowed us to calculate rates for disease metrics and to develop rate ratios showing dramatically higher rates among MSM than among other men or women. These data greatly improve our understanding of the disproportionate impact of these diseases among MSM in the U.S. and help with prevention planning.


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