Generalized Procedures for Testing Hypotheses about Survival or Recovery Rates

Comparisons of survival or recovery rates from different time periods or geographic regions may be difficult to accomplish using the Z-tests suggested by Brownie et al. (1985). We propose a general Chisquare statistic that addresses an unambiguous null hypothesis of homogeneity among several surviva...

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Bibliographic Details
Published in:The Journal of wildlife management 1989-01, Vol.53 (1), p.137-142
Main Authors: Sauer, John R., Williams, Byron K.
Format: Article
Language:English
Subjects:
Animal and plant ecology
Animal, plant and microbial ecology
Biological and medical sciences
Biology
Covariance matrices
Datasets
Degrees of freedom
Demecology
Estimation methods
Fundamental and applied biological sciences. Psychology
General aspects
Null hypothesis
Standard error
Statistical discrepancies
Statistics
Survival rates
Wildlife management
Wildlife population estimation
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Summary:Comparisons of survival or recovery rates from different time periods or geographic regions may be difficult to accomplish using the Z-tests suggested by Brownie et al. (1985). We propose a general Chisquare statistic that addresses an unambiguous null hypothesis of homogeneity among several survival or recovery rates. With this statistic, specific hypotheses of differences in rates can be simultaneously tested using contrasts. If necessary, a posteriori multiple comparisons can also be conducted that incorporate an adjustment for Type I error.
ISSN:0022-541X
1937-2817
DOI:10.2307/3801320