Øyvind Bakke

The exact unconditional z-pooled test for equality of two binomial probabilities: optimal choice of the Berger and Boos confidence coefficient

Exact unconditional tests for comparing two binomial probabilities are generally more powerful than conditional tests like Fishers exact test. Their power can be further increased by the Berger and Boos confidence interval method, where a p-value is found by restricting the common binomial probability under H 0 to a 1−γ confidence interval. We studied the average test power for the exact unconditional z-pooled test for a wide range of cases with balanced and unbalanced sample sizes, and significance levels 0.05 and 0.01. The detailed results are available online on the web. Among the values 10−3, 10−4, …, 10−10, the value γ=10−4 gave the highest power, or close to the highest power, in all the cases we looked at, and can be given as a general recommendation as an optimal γ.

Retrospective Studies of Red Deer Reproduction Using Regressing Luteal Structures

Reproduction is a key factor in understanding cervid population dynamics, and improved determination of reproduction may enhance our understanding of population performance as a basis for management decisions. We compared 2 approaches for retrospective analysis of red deer (Cervus elaphus atlanticus) reproduction, using regressing luteal structures as criteria for previous parturitions. Occurrence of a corpus rubrum (CR) proved a reliable criterion for assessing age-specific natality rates. Attempts to trace reproduction >1 year past on the basis of corpora albicantia (CA) led to increasing underestimation of past productivity when age increased, compared with known reproductive history or estimates of reproductive success according to accumulated age-specific natality rates. A model accounting for the rate of CA disappearance was useful in arriving at more accurate estimates for past productivity in older animals. J. WILDL. MANAGE. 58(4):654-663

Contextual and time dependent pain in fibromyalgia: An explorative study

BackgroundLittle is known about contextual effects on chronic pain, and how vulnerability factors influence pain in different contexts. We wanted to examine if fibromyalgia (FM) pain varied between two social contexts, i.e. at home versus in a doctor office, when it was measured the same day, and if pain was stable for 14 years when measured in similar contexts (doctor office). Our secondary aim was to explore if pain vulnerability factors varied in the two different contexts.FindingsFifty-five female FM patients were included in the study and scored pain in both contexts at baseline. Their age ranged between 21–68 years (mean 45.7), mean education level was 11 years and mean FM-duration was 15.6 years. Their mean pain was perceived significantly lower at home than in a doctor context the same day. However, pain was much more stable when measured in two similar contexts 14 year apart where 30 subjects (54.5%) completed. Predictor analyses revealed that pain vulnerability factors apparently varied by home and doctor contexts.ConclusionPain and pain predictors seem to vary by contexts and time, with less pain at home than to a doctor the same day, but with unchanged pain in the same context after 14 years. Thus, contextual pain cues should be accounted for when pain is measured and treated, e.g. by focusing more on home-measured pain and by optimizing the doctor office context. This explorative study should be followed up by a larger full-scale study.

Robust methods to detect disease-genotype association in genetic association studies: calculate p-values using exact conditional enumeration instead of simulated permutations or asymptotic approximations

Abstract In genetic association studies, detecting disease-genotype association is a primary goal. We study seven robust test statistics for such association when the underlying genetic model is unknown, for data on disease status (case or control) and genotype (three genotypes of a biallelic genetic marker). In such studies, p-values have predominantly been calculated by asymptotic approximations or by simulated permutations. We consider an exact method, conditional enumeration. When the number of simulated permutations tends to infinity, the permutation p-value approaches the conditional enumeration p-value, but calculating the latter is much more efficient than performing simulated permutations. We have studied case-control sample sizes with 500–5000 cases and 500–15,000 controls, and significance levels from 5×10–8 to 0.05, thus our results are applicable to genetic association studies with only a few genetic markers under study, intermediate follow-up studies, and genome-wide association studies. Our main findings are: (i) If all monotone genetic models are of interest, the best performance in the situations under study is achieved for the robust test statistics based on the maximum over a range of Cochran-Armitage trend tests with different scores and for the constrained likelihood ratio test. (ii) For significance levels below 0.05, for the test statistics under study, asymptotic approximations may give a test size up to 20 times the nominal level, and should therefore be used with caution. (iii) Calculating p-values based on exact conditional enumeration is a powerful, valid and computationally feasible approach, and we advocate its use in genetic association studies.

Preschool children's sickness absenteeism from Norwegian regular and outdoor day care centres: a comparative study.

Aims: To examine whether there are any differences in sickness absenteeism between children in outdoor day care centres and regular day care centres and also to investigate whether other variables predict sickness absenteeism. Methods: Data on sickness absence during a 4-week period together with several explanatory variables of 531 children in 32 regular and 37 outdoor day care centres were collected and included in the analysis. The data were analysed by generalized linear modelling. Results: The overall frequency of sickness absence was 5.1%. There was no general significant difference between sickness absenteeism in regular and outdoor day care centres. Of the other possible explanatory variables only two were found to contribute significantly: age, with a negative relationship, and the interaction effect of a child with a chronic disease or disability going to an outdoor day care centre, with a positive relationship. Conclusions: The present study indicates that sickness absenteeism of a child without a chronic disease or disability is not affected by whether the child attends a regular or an outdoor day care centre. There seem to be no health benefits for children with chronic diseases or disabilities to attend outdoor day care centres — there is in fact evidence that sickness absence for those children is higher in outdoor centres.