PubMed Health⌕ Search

Biomedical subjects

J P Buonaccorsi

Publications and source records attributed to J P Buonaccorsi.

6 recordsLinked to original sources
PubMed2001

Analysis of survival of young and old Aedes aegypti (Diptera: Culicidac) from Puerto Rico and Thailand.

It generally is assumed that the daily probability of survival of wild adult mosquitoes is independent of age. To test this assumption we conducted mark-release-recapture studies in Puerto Rico and Thailand to determine if estimated daily survival rates between two different age cohorts of the dengue vector Aedes aegypti (L.) were the same. Survivorship was estimated with nonlinear regression analysis using bootstrapping to obtain estimates of errors. Initial recapture success of the younger cohort was greater than the older cohort at both locations. Our analysis revealed a significantly greater survival rate for the younger cohort of females in Puerto Rico, and no significant differences between age cohorts in Thailand. For comparison, a traditional approach for analyzing these type of data, linear regression of log-transformed captures over time (exponential model), was used to calculate the probability of daily survival based on slopes of linear regression lines for recaptured mosquitoes. With this method, the estimated daily survival rate of older females (13-23 d old) was significantly greater than survival of younger ones (3-13 d old) in Puerto Rico and Thailand. In addition, short-range movement of mosquitoes was observed in Puerto Rico; maximum dispersal distance detected was 79 m. Survival rates of adult Ae. aegypti may be age-dependent and nonlinear regression analysis is a sensitive approach for comparing patterns of mosquito survival based on mark, single release, multiple recapture data.

Aedes↗
PubMed1998

Covariate measurement error and the estimation of random effect parameters in a mixed model for longitudinal data.

We explore the effects of measurement error in a time-varying covariate for a mixed model applied to a longitudinal study of plasma levels and dietary intake of beta-carotene. We derive a simple expression for the bias of large sample estimates of the variance of random effects in a longitudinal model for plasma levels when dietary intake is treated as a time-varying covariate subject to measurement error. In general, estimates for these variances made without consideration of measurement error are biased positively, unlike estimates for the slope coefficients which tend to be 'attenuated'. If we can assume that the residuals from a longitudinal fit for the time-varying covariate behave like measurement errors, we can estimate the original parameters without the need for additional validation or reliability studies. We propose a method to test this assumption and show that the assumption is reasonable for the example data. We then use a likelihood-based method of estimation that involves a simple extension of existing methods for fitting mixed models. Simulations illustrate the properties estimators.

Analysis of Variance↗
PubMed1995

Prediction in the presence of measurement error: general discussion and an example predicting defoliation.

Motivated by the particular problem of predicting defoliation based on a measure of gypsy moth egg mass density, prediction in the presence of measurement error is discussed. The measurement error variances and covariances are allowed to vary from unit to unit and are estimated by some type of within unit sampling. A general discussion is given as to when one should correct for the measurement error, and a method of estimating the prediction standard deviation is given when a correction is needed. The results are illustrated with the defoliation example.

Animals↗
PubMed1993

Dynamics of biomass partitioning in field-grown radish varieties, treated with ethylenediurea.

During the growing season of 1990, five staggered crops of radish (Raphanus sativus L.) were grown in the field, using the cultivars 'Cherry Belle', 'Red Prince', and 'Red Devil B'. Half of the plants received a soil drench (100 ml plant(-1); 100 mg litre(-1) of ethylenediurea (EDU) once, early in plant development. Destructive harvests were carried out at 2-day intervals during vegetative development. Non-linear growth kinetics, derived from Richards' function, were fitted to the dry weight data of the total plant, main organs (shoot and hypocotyl) and to the dry weight ratio between below-ground and above-ground organs. Estimating the parameters of these non-linear functions and testing their differences between EDU-treated and untreated plants unveiled biologically meaningful information on the impact of different levels of ambient ozone (O(3)) during the growth periods. The modified function which was applied to the data of biomass partitioning between the major plant parts was more powerful in detecting transient alterations in assimilate allocation compared to the growth dynamics of individual plant organs. At low levels of O(3), biomass partitioning towards the below-ground sink organs was slightly delayed and finally restricted in EDU-treated plants. When ambient O(3) reached moderate levels, which did not cause visible foliar injury, assimilate partitioning between organs was only insignificantly altered during early growth when EDU-treatments were compared. As growth progressed, however, less assimilates were allocated towards the hypocotyl and roots in the plants not protected by EDU. This pattern was similar in all cultivars tested, but was smallest in 'Cherry Belle', which is known to be sensitive to O(3) with respect to foliar injury. During the 15- to 19-day periods of rapid growth, the O(3)-exposure >80 nl litre(-1) ranged from 0.015 to 0.209 microl litre(-1) O(3) h, which corresponds to 7 h d(-1) mean values between 40 and 50 nl litre(-1) O(3), confirming that ambient ozone did not exceed a moderate level in this study.

Journal Article↗
PubMed1986

Designs for slope ratio assays.

Optimal designs are obtained for the estimation of relative potency in a slope ratio assay. Three criteria are considered based on the asymptotic variance of the standard point estimator. Efficiency functions are derived and numerical examples are given.

Biometry↗