Means Procedure Research Articles

EVALUATION OF CARROT GENETIC SUBSTRUCTURE: COMPARISON OF THE EFFICIENCY OF MAPPED MOLECULAR MARKERS WITH RANDOMLY CHOSEN MARKERS

ISHS International Symposium on Molecular Markers for Characterizing Genotypes and Identifying Cultivars in Horticulture EVALUATION OF CARROT GENETIC SUBSTRUCTURE: COMPARISON OF THE EFFICIENCY OF MAPPED MOLECULAR MARKERS WITH RANDOMLY CHOSEN MARKERS

Determination of sample size for selecting the smallest of k poisson population means

A procedure for selecting a Poisson population with smallest mean is considered using an indifference zone approach. The objective is to determine the smallest sample size n required from k ≥ 2 populations in order to attain the desired probability of correct selection. Since the means procedure is not consistent with respect to the difference or ratio alone, two distance measures are used simultaneously to overcome the difficulty in obtaining the smallest probability of correct selection that is greater than some specified limit. The constants required to determine n are computed and tabulated. The asymptotic results are derived using a normal approximation. A comparison with the exact results indicates that the proposed approximation works well. Only in the extreme cases small increases in n are observed. An example of industrial accident data is used to illustrate this procedure.

Battelle Developmental Inventory

In 1986, Congress passed Public Law 99–457, which provided incentives for states to develop early childhood intervention programs for qualified infants and toddlers from birth through 2 years of age and their families. The law later became known as the Individuals With Disabilities Education Act (IDEA),1 and, with the 1997 amendments, the early intervention program became Part C of the Act. Part C of IDEA defines the terms “evaluation” and “assessment” as they relate to early intervention programs. “Evaluation” means procedures used to determine a child's initial and continuing eligibility for services. Eligibility criteria are defined by each state, but they typically include documentation of delay in one or more areas of development listed in the federal law, including cognitive, adaptive (self-help), physical (eg, gross and fine motor), communication, and social-emotional development. “Assessment” is defined as ongoing procedures to identify a child's strengths and needs, and the services required to meet those needs. This is the process of program planning. Evaluation requires what Kirshner and Guyatt referred to as a “discriminative index,” which distinguishes “between individuals or groups on an underlying dimension when no external criterion or gold standard is available for validating these measures.”2 Measures useful for determining a child's eligibility for services are those that can be used to differentiate between children who have developmental delays and children who do not have such delays.3 Discriminative measures include test items that distinguish between children of varying ages, such as stacking blocks or jumping down from a step. Although such information is can be useful for determining whether a child has a developmental delay, knowledge that a child can or cannot perform such test items often is not useful for program planning purposes. Program planning often requires identification of goals specific to an individual, particularly when intervention …

Designing Organizational Memories: Concept and Method

Organizational memory, has become a popular theme in management studies, leading to theoretically valuable conceptualizations, which, however, often fail in their practical usability. Recently, organizational memory has also become a topic in the field of information systems. This article tries to bridge the gap between these organizational conceptualizations and information systems by proposing methods for organizational memory contents (knowledge and information) analysis and the analysis of organizational memory means (procedures and media). These methods describe an approach to organizational memory design that, according to the author, should be complemented by methods for organizational memory evolution. The design approach is further clarified by a case scenario.

Evaluation of Insecticides for Control of Corn Earworm on Sweet Corn, 1997

Abstract The study was located at the University of Arkansas Main Experimental Station, Fayetteville. Plot was a single 50-ft-long row. Single buffer rows separated plots. Insecticides were ap-plied with a backpack sprayer equipped with 1 Tee Jet 8003 nozzle calibrated to deliver 34.5 gpa at 30 psi. Treatments were applied 15, 18, 21, 24, and 27 Aug in a RCB design with 4 replications. Plots were harvested on 29 Aug and ears were rated for damage: good (no CEW damage), damaged (ears with damage confined to the apical inch), and cull (ears with damage past the apical inch). Live CEW larvae within each ear were also counted. Data were analyzed with SAS Proc ANOVA and means of good, marketable (good + damaged ears), and larvae per ear were separated by LSD.

Evaluation of the one-sided percentage points of the singular multivariate normal distribution

This paper presents a new theorem, as a substitute for existing results which are shown to have some errors, for evaluating the exact one-sided percentage points of the multivariate normal distribution with a singular negative product correlation structure. By extending the result from the multivariate normal distribution to the multivariate t-distribution with corresponding singular correlation structure, we tabulate the one-sided critical points for the Analysis of Means procedure.

Conducting Meta-Analysis Using the Proc Means Procedure in Sas

The methodology for using the PROC MEANS procedure in SAS to perform the data computations called for by the Hunter and Schmidt approach to meta-analysis is presented. Using SAS for meta-analytic data analysis offers several potential advantages including ease of use, flexibility, and widespread availability. Specific procedures are presented for calculating summary statistics and then correcting these summary statistics for sampling error and other statistical artifacts such as range restriction and measurement error. One particularly attractive feature of this approach is the ease with which potential moderator variables can be analyzed simply by adding a few additional statements to the SAS program.

Semirange tests for shortfall

When any ‘test of significance’ is considered in relation to a set of fully specified statistical alternatives, formal resemblance to a ‘test of hypothesis’ appears. A suite of tests of significance that bears such a formal resemblance to the means procedure for subset selection is developed. The development exposes a flaw in the traditional theories of statistical testing. Removal of the flaw results in a new theory of ‘testing’. The outcome is useful when trying to judge whether or not any particular one of a number of entries in a given statistical trial might have been amongst ‘the best’ of those entries.

Analysis of Lattice Design Using PC-SAS

(...) This simple SAS program provides a way of analyzing lattice design PROC GLM, PROC MEANS, and data manipulations. This program required ≃ 8 min to analyze these data in an IBM-compatible AT computer (...)

Wettability of a hydrophilic addition silicone impression material

Silicone impression materials, long noted for their poor wettability, have typically demonstrated contact angles with water greater than 90 degrees. This study compared the wettability of a new hydrophilic addition silicone with that of other impression materials. Specimens from various viscosities of polyether, polysulfide, hydrophobic addition silicone, and hydrophilic addition silicone were formed against a smooth surface. The advancing contact angle of a saturated aqueous solution of CaSO 4 on the impression materials was measured after 1 minute. Mean contact angles were calculated and results were analyzed by ANOVA and a multiple comparison of means procedure. Differences between pairs of contact angle means were found to be statistically significant except for the polyether-hydrophilic addition silicone pair. The wettability of the hydrophilic addition silicone impression material was found to be not significantly different from that of a polyether impression material.

Testing for Interactions Using the Analysis of Means

An analysis of means (ANOM) procedure is suggested for testing the significance of two-factor interactions in fixed-effects balanced designs. When at least one factor is at only two levels, the suggested procedure uses the exact critical points for the ANOM. New critical points are given for the case in which both factors are at more than two but fewer than six levels. The procedure can be extended to higher-order interactions, but the quantities being plotted become so complex that they are of little use in assessing practical significance.

An asymptotic distribution-free selection procedure for a two-way layout problem

This paper deals with an asymptotic distribution-free subset selection procedure for a two-way layout problem. The treatment effect with the largest unknown value is of interest to us. The block effect is a nuisance parameter in this problem. The proposed procedure is based on the Hodges-Lehmann estimators of location parameters. The asymptotic relative efficiency of the proposed procedure with the normal means procedure is evaluated. It is shown that the proposed procedure has a high efficiency.

Differences in seed longevity at the species level

Abstract Published seed storage data for 92 species derived from 13 localities were subjected to probit analysis to determine the half‐viability period (P50) for each sample. Estimates of half‐viability period for each species averaged over all 13 localities were calculated using a least square means procedure applied to known values for the half‐viability period for each species at each of its storage stations. The results reported here represent an initial step in the objective organization of seed longevity data.

A comparison of selection procedures for selecting the best normal population under heterogeneity of variance

This study examines the comparative probabilities of making a correct selection when using the means procedure (M), the medians procedure (D) and the rank-sum procedure (S) to correctly select the normal population with the largest mean under heterogeneity of variance. The comparison is conducted by using Monte-Carlo simulation techniques for 3, 4, and 5 normal populations under the condition that equal sample sizes are taken from each population. The population means and standard deviations are assumed to be equally-spaced. Two types of heterogeneity of variance are considered: (1) associating larger means with larger variances, and (2) associating larger means with smaller variances.

On rules based on sample medians for selection of the largest location parameter

The problem of selection of a subset containing the largest of several location parameters is considered, and a Gupta-type selection rule based on sample medians is investigated for normal and double exponential populations. Numerical comparisons between rules based on medians and means of small samples are made for normal and contaminated normal populations, assuming the popula-tion means to be equally spaced. It appears that the rule based on sample means loses its superiority over the rule based on sample medians in case the samples are heavily contaminated. The asymptotic relative efficiency (ARE) of the medians procedure relative to the means procedure is also computed, assuming the normal means to be in a slippage configuration. The means proce-dure is found to be superior to the median procedure in the sense of ARE. As in the small sample case, the situation is reversed if the normal populations are highly contaminate.

Bayesian subset selection for additive and linear loss function

Given k independent samples of common size n from k populations πj,…,πk with distribution the problem is to select a non-empty subset form {πj,…,πk}, which is associated with good (large) θ-values. We consider this problem from a Bayesian approach. By choosing additive and especially linear loss functions we try to fill a gap lying in between the results of Deely and Gupta (1968) and more recent papers due to Goel and Rubin (1977), Gupta and Hsu (1978) and other authors. It is shown that under acertain normal model Seal's procedure turns out to be Bayes w.r.t. an unrealistic loss function where as Gupta's maximunl means procedure turns out to be ( for large n) asymptotically Bayes w.r. t. more realistic additive loss functions. Finally, in the appendix sonie bounds for are derived (where are fixed known and to approximate the Bayes rules w.r.t. linear loss functions in cases where n is finite.

An Adaptive M-Estimator and Its Application to a Selection Problem

A robust adaptive estimation procedure for location estimation problems is developed. Classification in this procedure is done on the basis of skewness and tailweight, using two statistics that are ratios of linear functions of sample order statistics. The associated estimators are of the general type known as M-estimators, Following the development of the adaptive location estimation procedure, an application to the k population selection problem is given. Monte Carlo results show the superiority of the adaptive procedure to the sample means procedure, the rank sum procedure, and the previously developed adaptive procedure of Randles, Ramberg, and Hogg.

An Adaptive M-Estimator and Its Application to a Selection Problem

A robust adaptive estimation procedure for location estimation problems is developed. Classification in this procedure is done on the basis of skewness and tailweight, using two statistics that are ratios of linear functions of sample order statistics. The associated estimators are of the general type known as M-estimators, Following the development of the adaptive location estimation procedure, an application to the k population selection problem is given. Monte Carlo results show the superiority of the adaptive procedure to the sample means procedure, the rank sum procedure, and the previously developed adaptive procedure of Randles, Ramberg, and Hogg.

An Adaptive Procedure for Selecting the Population with Largest Location Parameter

An adaptive procedure for selecting the population with the largest (smallest) location parameter is given. A Monte Carlo sampling study is presented indicating that this procedure performs as well as the means procedure when the underlying distribution is medium tailed like the normal. It is shown to be superior to both the means procedure and the rank sum procedure when the underlying distribution is either very light tailed (e.g., the uniform distribution) or very heavy tailed (e.g., the Cauchy distribution).

An Adaptive Procedure for Selecting the Population With Largest Location Parameter

An adaptive procedure for selecting the population with the largest (smallest) location parameter is given. A Monte Carlo sampling study is presented indicating that this procedure performs as well as the means procedure when the underlying distribution is medium tailed like the normal. It is shown to be superior to both the means procedure and the rank sum procedure when the underlying distribution is either very light tailed (e.g., the uniform distribution) or very heavy tailed (e.g., the Cauchy distribution).