Selecting the Best Population,Provided It Is Better than a Control: The Unequal Variance Case

Bechhofer and Turnbull (1978) proposed two procedures to compare k normal means with a standard and the procedures guarantee that (1) with probability at least P₀* (specified), no category is selected when the best experimental category is sufficiently worst than the standard, and (2) with probability at least P₁* (specified), the best experimental category is selected when it is sufficiently better than the second best and the standard. For the case of common known variance, they studied a single-stage procedure. For the case of common unknown variance, they studied a two-stage procedure. Under the same formulation of Bechhofer and Turnbull (1978) and for the same selection goals (1) and (2) described above, Wilcox (1984a) proposed a procedure to the case of unknown and unequal variances, and supplied a table of the necessary constants to implement the procedure. This paper considers the case of unknown and unequal variances for the same formulation of Bechhofer and Turnbull, and Wilcox, but assumes that μ₀ is an unknown control. A two-stage procedure is proposed to solve the problem. A lower bound of the probability of a correct selection is derived and it takes the same form as the double integral appeared in Rinott (1978) which was used for the lower bound of the probability of a correct selection for a different selection goal.     

Experimental Design for Bayesian Estimations in the Linear Regression Model Taking Costs into Account

It is assumed that a known, correct, linear regression model (model I) is given. Let the problem be based on a Bayesian estimation of the regression parameter so that any available a priori information regarding this parameter can be used. This Bayesian estimation is, squared loss, an optimal strategy for the overall problem, which is divided into an estimation and a design problem. For practical reasons, the effort involved in performing the experiment will be taken into account as costs. In other words, the experimental design must result in the greatest possible accuracy for a given total cost (restriction of the sample size n). The linear cost function k(x) = 1 + c (x - a)/(b - a) is used to construct costoptimal experimental designs for simple linear regression by means of V = H = [a, b] in a way similar to that used for classical optimality criteria. The complicated structures of these designs and the difficulty in determining them by a direct approach have made it appear advisable to describe an iterative procedure for the construction of cost-optimal designs.     

Estimation of amniotic fluid phospholipids by high-performance liquid chromatography

We have developed a high-performance liquid chromatographic (HPLC) method for the analyses of surface-active amniotic fluid phospholipids, lecithin (L), sphingomyelin (S), phosphatidyl glycerol (PG), phosphatidyl inositol (PI), phosphatidyl ethanolamine (PE), and phosphatidyl serine (PS), which are important in the prediction of fetal lung maturity. The method incorporates an internal standard in the amniotic fluid extract, and utilizes a 10-μl aliquot of a 2:1 chloroform—methanol extract of amniotic fluid injected onto a 5-μm DIOL or CN HPLC column, and a variable-wavelength detector set at 203 nm.Amniotic fluid phospholipid estimations were determined on 40 amniotic fluid samples by the HPLC method and by the routine thin-layer chromatographic (TLC) method. Good agreement was observed between the two methods for the L/S ratio, PG, and PI (r_PG 0.94, r_PI 0.95, r_L/S 0.97).The advantages of the HPLC procedure include: (i) Selective separation for PG, PI, PS, and PE, as well as L and S at the same time. (ii) The internal standard allows individual concentration of phospholipids to be estimated. (iii) The procedure is rapid: 16 min for a single assay compared with 50 min for the standard TLC procedure.     

A note on familywise error rate for a primary and secondary endpoint

Hung et al. (2007) considered the problem of controlling the type I error rate for a primary and secondary endpoint in a clinical trial using a gatekeeping approach in which the secondary endpoint is tested only if the primary endpoint crosses its monitoring boundary. They considered a two-look trial and showed by simulation that the naive method of testing the secondary endpoint at full level α at the time the primary endpoint reaches statistical significance does not control the familywise error rate at level α. Tamhane et al. (2010) derived analytic expressions for familywise error rate and power and confirmed the inflated error rate of the naive approach. Nonetheless, many people mistakenly believe that the closure principle can be used to prove that the naive procedure controls the familywise error rate. The purpose of this note is to explain in greater detail why there is a problem with the naive approach and show that the degree of alpha inflation can be as high as that of unadjusted monitoring of a single endpoint.     

A modified DNA isolation protocol for obtaining pure RT-PCR grade RNA

We provide a simple but very efficient method for RNA preparation from Saccharomyces cerevisiae based on a standard chromosomal DNA isolation protocol. The method yields DNA-free total RNA, including mRNA, rRNA, and tRNA but can easily be adjusted to considerably enrich low molecular weight RNAs, such as tRNAs and the small rRNA species (5S and 5.8S). The procedure was proven and validated by verification of cDNAs belonging to four different genes, two of which encoding polypeptides and two tRNA genes. Besides its simpleness, the method is further advantagous in terms of safety (omitting hazardous phenol) and cost efficiency.     

Predictive Estimation of Finite Population Mean Using a Product Estimator for Two-Stage Sampling

In an attempt to estimate a finite population mean under the predictive approach described in Basu (1971) through the product method of estimation, we created a new product-type estimator for a two-stage sampling procedure. We also report a simulation study that is made in order to understand better the performance of the new estimator compared to the classical product estimator.     

A response-adaptive randomization procedure for multi-armed clinical trials with normally distributed outcomes

We propose a novel response-adaptive randomization procedure for multi-armed trials with continuous outcomes that are assumed to be normally distributed. Our proposed rule is non-myopic, and oriented toward a patient benefit objective, yet maintains computational feasibility. We derive our response-adaptive algorithm based on the Gittins index for the multi-armed bandit problem, as a modification of the method first introduced in Villar et al. (Biometrics, 71, pp. 969-978). The resulting procedure can be implemented under the assumption of both known or unknown variance. We illustrate the proposed procedure by simulations in the context of phase II cancer trials. Our results show that, in a multi-armed setting, there are efficiency and patient benefit gains of using a response-adaptive allocation procedure with a continuous endpoint instead of a binary one. These gains persist even if an anticipated low rate of missing data due to deaths, dropouts, or complete responses is imputed online through a procedure first introduced in this paper. Additionally, we discuss how there are response-adaptive designs that outperform the traditional equal randomized design both in terms of efficiency and patient benefit measures in the multi-armed trial context.     

A Confidence‐Limit‐Based Approach to the Assessment of Hardy–Weinberg Equilibrium

The classical χ²‐procedure for the assessment of Hardy–Weinberg equilibrium (HWE) is tailored for detecting violations of HWE. However, many applications in genetic epidemiology require approximate compatibility with HWE. In a previous contribution to the field (Wellek, S. (2004). Biometrics, 60 , 694–703), the methodology of statistical equivalence testing was exploited for the construction of tests for problems in which the assumption of approximate compatibility of a given genotype distribution with HWE plays the role of the alternative hypothesis one aims to establish. In this article, we propose a procedure serving the same purpose but relying on confidence limits rather than critical bounds of a significance test. Interval estimation relates to essentially the same parametric function that was previously chosen as the target parameter for constructing an exact conditional UMPU test for equivalence with a HWE conforming genotype distribution. This population parameter is shown to have a direct genetic interpretation as a measure of relative excess heterozygosity. Confidence limits are constructed using both asymptotic and exact methods. The new approach is illustrated by reanalyzing genotype distributions obtained from published genetic association studies, and detailed guidance for choosing the equivalence margin is provided. The methods have been implemented in freely available SAS macros.     

Ranked Set Sampling and the Line Intercept Method: A More Efficient Procedure

Ranked set sampling is a method which may be used to increase the efficiency of the estimator of the mean of a population. Ranked set sampling with size biased probability of selection (i.e., the items are selected with probability proportion to its size) is combined with the line intercept method to increase the efficency of estimating cover, density and total amount of some variable of interest (e.g. biomass). A two-stage sampling plan is suggested with line intercept sampling in the first stage. Simple random sampling and ranked set sampling are compared in the second stage to show that the unbiased estimators of density, cover and total amount of some variable of interest based on ranked set sampling have smaller variances than the usual unbiased estimator based on simple random sampling. Efficiency is increased by reducing the number of items which are measured on a transect or by increasing the number of independent transects utilized in a study area. An application procedure is given for estimation of coverage, density and number of stems of mountain mahogany (Cercocarpus montanus) in a study area east of Laramie, Wyoming.     

A two-stage stepwise estimation procedure

Summary .   This article proposes a two-stage simultaneous confidence procedure for the comparisons of k pairs of population means, without using multiplicity adjustment of more than two populations. The proposed procedure can be broadly applied to parametric or nonparametric models. It is robust and versatile because its derivation only utilizes a partitioning approach in conjunction with a bivariate adjustment, without any assumption on the underlying distribution. To elucidate the application, the proposed procedure is intertwined with the estimation of the therapeutic window of a drug. It provides confidence limits for the efficacy and the toxicity of the effective doses, highest ineffective dose, safe doses, and lowest unsafe dose, simultaneously. Such estimation information facilitates follow-up studies in clinical trials. As an illustrative example, the new procedure is applied to analyze a data set on molecular cancer therapeutics regarding the apoptotic killing effects of different chemical compounds on two leukemia cell lines.     

Nucleosome DNA Bendability Matrix (C. elegans)

Abstract

An original signal extraction procedure is applied to database of 146 base nucleosome core DNA sequences from C. elegans (S. M. Johnson et al. Genome Research 16, 1505–1516, 2006). The positional preferences of various dinucleotides within the 10.4 base nucleosome DNA repeat are calculated, resulting in derivation of the nucleosome DNA bendability matrix of 16x10 elements. A simplified one-line presentation of the matrix (“consensus” repeat) is…A(TTTCCGGAAA)T…. All 6 chromosomes of C. elegans conform to the bendability pattern. The strongest affinity to their respective positions is displayed by dinucleotides AT and CG, separated within the repeat by 5 bases. The derived pattern makes a basis for sequence-directed mapping of nucleosome positions in the genome of C. elegans. As the first complete matrix of bendability available the pattern may serve for iterative calculations of the species-specific matrices of bendability applicable to other genomic sequences.     

Soil characteristics and nitrogen resorption in Stipa krylovii native to northern China

Nitrogen (N) resorption from senescing tissues enables plants to conserve and reuse this important nutrient. As such, it is expected that plant species adapted to infertile soils could have a higher N-resorption efficiency (percentage reduction of nitrogen between green and senescing tissues) and/or higher N-resorption proficiency (absolute reduction of nitrogen in senescing tissues) than those adapted to fertile soils. To test this hypothesis, we investigated the relationships among soil characteristics (total N, nitrate-N, ammonium-N, pH and moisture) and N resorption in Stipa kryloviiRoshev., a species occurred widely in natural grasslands of northern China. N contents in green and senescing tissues were 6.7±0.1 and 3.3±0.1 mg g^–1, respectively. The mean value of N-resorption efficiency was found to be 72.1%. The N-resorption efficiency in S. kryloviiwas independent of soil characteristics. The N-resorption proficiency in S. kryloviiwas dependent on soil nitrate- and ammonium-N, but it was relatively independent of soil total N. The N-resorption proficiency was negatively correlated with soil pH and moisture. There was a positive correlation between N concentration in green tissues and resorption efficiency. However, N-resorption efficiency was not correlated significantly with N concentration in senescing tissues. These results indicate that the intraspecific variation in N resorption of Stipa kryloviiRoshev. is associated with soil regimes and that higher N resorption on N-poor soils is an adaptive strategy for S. kryloviito maximize N use under conditions of limited N supply.     

Simplified, rapid and inexpensive extraction procedure for a high-performance liquid chromatographic method for determination of disopyramide and its main metabolite mono-N-dealkylated disopyramide in serum

A simplified, rapid and inexpensive extraction procedure for the determination of the antiarrhythmic drug disopyramide and its main metabolite mono-N-desalkylated disopyramide in serum by high-performance liquid chromatography has been developed. The analysis uses ultraviolet detection at 254 nm, and a 5 μm reversed-phase column with a mobile phase of water—triethylamine—acetonitrile—PIC-B8 reagent. Serum extraction is performed with dichloromethane and 1 M sodium hydroxide. p-Chlorodisopyramide is used as internal standard. Recovery rates were 94.5% (S.D. 5.7%) for disopyramide, 96.8% (S.D. 2.2%) for mono-N-desalkylated disopyramide and 97.9% (S.D. 2.8%) for the internal standard.     

Antimicrobial breakpoint estimation accounting for variability in pharmacokinetics

Background  

Pharmacokinetic and pharmacodynamic (PK/PD) indices are increasingly being used in the microbiological field to assess the efficacy of a dosing regimen. In contrast to methods using MIC, PK/PD-based methods reflect in vivo conditions and are more predictive of efficacy. Unfortunately, they entail the use of one PK-derived value such as AUC or Cmax and may thus lead to biased efficiency information when the variability is large. The aim of the present work was to evaluate the efficacy of a treatment by adjusting classical breakpoint estimation methods to the situation of variable PK profiles.     

Disinfectant test against monoculture and mixed-culture biofilms composed of technological, spoilage and pathogenic bacteria: bactericidal effect of essential oil and hydrosol of Satureja thymbra and comparison with standard acid-base sanitizers

Aims: To assess the antimicrobial action of three natural‐derived products (essential oil, decoction and hydrosol of Satureja thymbra) against biofilms, composed of useful, spoilage and pathogenic bacteria (formed as monoculture or/and mixed‐culture), and to compare their efficiency with three standard acid and alkaline chemical disinfectants. Methods and Results: Two acids (hydrochloric and lactic, pH 3), one alkali (sodium hydroxide, pH 11), the essential oil of S. thymbra (1% v/v) and the two by‐products of the essential oil purification procedure (the decoction and the hydrosol fraction of essential oil, 100%), were tested against biofilms formed by five bacterial species, either as monospecies, or as mixed‐culture of all species. The tested bacterial species were Staphylococcus simulans and Lactobacillus fermentum (useful technological bacteria), Pseudomonas putida (spoilage bacterium), Salmonella enterica and Listeria monocytogenes (pathogenic bacteria). Biofilms were left to be formed on stainless steel coupons for 5 days at 16°C, before the application of disinfection treatments, for 60 and 180 min. The disinfection efficiency was evaluated by detaching the remaining viable biofilm cells and enumerating them by agar plating, as well as by automated conductance measurements (using Rapid Automated Bacterial Impedance Technique). Both these methods revealed that the essential oil and the hydrosol of S. thymbra exhibited a strong antimicrobial action against both monospecies and mixed‐culture biofilms. Surprisingly, the efficiency of the other three acid–base disinfectants was not adequate, although a long antimicrobial treatment was applied (180 min). Conclusions: The essential oil of S. thymbra (1%), as well as its hydrosol fraction (100%), presents sufficient bactericidal effect on bacterial biofilms formed on stainless steel. Significance and Impact of the Study: Use of natural antimicrobial agents could provide alternative or supplemented ways for the disinfection of microbial‐contaminated industrial surfaces.     

A comparative study of the lipid composition of yeasts with different fermentative capacities

Summary The lipid composition of a classical yeast and a poor fermenter, at low and high sugar concentrations, was compared. Polyunsaturated fatty acids (18:2, 18:3) were found in the osmotolerant weak fermenter, Saccharomyces mellis, their content decreasing with an increase of glucose levels, while the highly fermenting yeast S. cerevisiae had no polyunsaturated fatty acids at all sugar concentrations examined. Also total unsaturation of fatty acids ( mol^–1) was significantly higher with S. mellis. The sterol content varied considerably, being higher with the highly fermenting yeasts and low with S. mellis and the film yeast Pichia sp. The ratio of free sterols/phospholipids was high in S. cerevisiae (1:7) and low in S. mellis (1:177). Hybrid yeasts (S. cerevisiaexS. mellis) which were the best fermenting organisms in our study, also showed a high ratio of free sterols/phospholipids (1:6–1:8). A correlation between the fermentative capacity of yeasts and the fluidity of their membranes is suggested.     

Further Results in Estimating the Classification Error in Discriminance Analysis

Basing on the approach by McLachlan (1977) a procedure for the conditional and common error estimation of the classification error in discriminance analysis is described for k ≧ 2 classes. As a rapid procedure for large sample sizes and feature numbers, a modification of the resubstitution method is proposed being favourable with respect to computing time. Both methods provide useful estimations for the probability of misclassification. In calculating the weighting function w, deviations from preconditions known from the MANOVA such as the skewness, the truncation or the inequality of the covariance matrices, hardly play any role; it appears that only a variation of the sample sizes of the classes substantially influences the weighting functions. The error rates of the tested error estimation methods likewise in effect depend on the sample sizes of the classes. Violations of the mentioned preconditions in the form described above result in different variations of the error estimates, depending on these sample sizes. A comparison between error estimation and allocation relative to a simulated population demonstrates the goodness of the used error estimation procedures.     

Biology of the leaf roller <Emphasis Type="Italic">Salbia lotanalis</Emphasis> and its impact on the invasive tree <Emphasis Type="Italic">Miconia calvescens</Emphasis>

Miconia calvescens (Melastomataceae) is an invasive alien tree in native forests on some Pacific islands and a potentially invasive species in Australia. Searches for potential classical biocontrol agents have been undertaken for over a decade in the centre of origin (Central and South America). Salbia lotanalis (Lepidoptera: Pyralidae) is a leaf roller which has been recognized as a promising classical biocontrol agent for M. calvescens. This paper presents the biology and an impact study of S. lotanalis on M. calvescens. Life table parameters showed that S. lotanalis has a high reproductive capacity, with up to six generations a year. Miconia calvescens seedlings attacked by S. lotanalis caterpillars had their growth rate significantly reduced. Seedlings subjected initially to a high level of defoliation (80%) caused by caterpillars had leaf fall and a lower leaf area than controls after 210 days. Considering the high population growth rate and significant impact on young plants, S. lotanalis appears to have a high potential for use as a classical biological control agent to be used against M. calvescens.