TY - JOUR
T1 - Assessing overdispersion and dose-response in the male dominant lethal assay
AU - Lockhart, Ann Marie C.
AU - Piegorsch, Walter W.
AU - Bishop, Jack B.
PY - 1992/8
Y1 - 1992/8
N2 - In dominant lethal studies the primary variables of interest are typically expressed as discrete counts or proportions (e.g., live implants, resorptions, percent pregnant). Simple statistical sampling models for discrete data such as binomial or Poisson generally do not fit this type of data because of extra-binomial or extra-Poisson departures from variability predicted under these simple models. Extra-variability in the fetal response may originate from parental contributions. These can lead to over- or under-dispersion seen as, e.g., extra-binomial variability in the proportion response. Utilizing a large control database, we investigated the relative impact of extra-variability from male or female contributions on the endpoints of interest. Male-related effects did not seem to contribute to overdispersion in our database; female-related effects were, however, evidenced. Various statistical methods were considered to test for significant treatment differences under these forms of sampling variability. Computer simulations were used to evaluate these methods and to determine which are most appropriate for practical use in the evaluation of dominant lethal data. Our results suggest that distribution-free statistical methods such as a nonparametric permutation test or rank-based tests for trend can be recommended for use.
AB - In dominant lethal studies the primary variables of interest are typically expressed as discrete counts or proportions (e.g., live implants, resorptions, percent pregnant). Simple statistical sampling models for discrete data such as binomial or Poisson generally do not fit this type of data because of extra-binomial or extra-Poisson departures from variability predicted under these simple models. Extra-variability in the fetal response may originate from parental contributions. These can lead to over- or under-dispersion seen as, e.g., extra-binomial variability in the proportion response. Utilizing a large control database, we investigated the relative impact of extra-variability from male or female contributions on the endpoints of interest. Male-related effects did not seem to contribute to overdispersion in our database; female-related effects were, however, evidenced. Various statistical methods were considered to test for significant treatment differences under these forms of sampling variability. Computer simulations were used to evaluate these methods and to determine which are most appropriate for practical use in the evaluation of dominant lethal data. Our results suggest that distribution-free statistical methods such as a nonparametric permutation test or rank-based tests for trend can be recommended for use.
KW - Dose-response analysis
KW - Extra-binomial variability
KW - Germ-cell mutagenesis
KW - Heritable disease
KW - Litter effect
KW - Mouse
KW - Statistical methods
KW - Under-dispersion
UR - http://www.scopus.com/inward/record.url?scp=0026686315&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0026686315&partnerID=8YFLogxK
U2 - 10.1016/0165-1161(92)90007-9
DO - 10.1016/0165-1161(92)90007-9
M3 - Article
C2 - 1380118
AN - SCOPUS:0026686315
VL - 272
SP - 35
EP - 58
JO - Mutation Research - Environmental Mutagenesis and Related Subjects Including Methodology
JF - Mutation Research - Environmental Mutagenesis and Related Subjects Including Methodology
SN - 0165-1161
IS - 1
ER -