Greater Number Of Replications Research Articles

Lot-to-lot reagent verification: Effect of sample size and replicate measurement on linear regression approaches

BackgroundWe investigate the simulated impact of varying sample size and replicate number using ordinary least squares (OLS) and Deming regression (DR) in both weighted and unweighted forms, when applied to paired measurements in lot-to-lot verification. MethodsSimulation parameter investigated in this study were: range ratio, analytical coefficient of variation, sample size, replicates, alpha (level of significance) and constant and proportional biases. For each simulation scenario, 10,000 iterations were performed, and the average probability of bias detection was determined. ResultsGenerally, the weighted forms of regression significantly outperformed the unweighted forms for bias detection. At the low range ratio (1:10), for both weighted OLS and DR, improved bias detection was observed with greater number of replicates, than increasing the number of comparison samples. At the high range ratio (1:1000), for both weighted OLS and DR, increasing the number of replicates above two is only slightly more advantageous in the scenarios examined. Increasing the numbers of comparison samples resulted in better detection of smaller biases between reagent lots. ConclusionsThe results of this study allow laboratories to determine a tailored approach to lot-to-lot verification studies, balancing the number of replicates and comparison samples with the analytical performance of measurement procedures involved.

REFERENCE INTERVALS FOR PLASMA BIOCHEMISTRY OF HEMOLYMPH IN SUBADULT CHILEAN ROSE TARANTULA (GRAMMASTOLA ROSEA) UNDER CHEMICAL RESTRAINT.

Tarantulas are a commonly kept species that are occasionally presented to veterinarians in exotic practice. A recent study on Grammastola rosea hemolymph biochemistry has been performed with nonanesthetized adult theraphosids. The objective of this study was to produce reference intervals for biochemistry biomarkers in hemolymph of chemically restrained G. rosea for use diagnostically by exotic veterinarians. Cardiac hemolymph collection was performed on 20 subadult tarantulas under general anesthesia with isoflurane. Samples were processed by a commercial laboratory. Statistics performed on the data include outlier exclusion, descriptive statistics, normality tests, and Pearson correlations. Reference intervals were made for total protein, creatine kinase (CK), aspartate aminotransferase (AST), glucose, uric acid (UA), calcium, and phosphorus. No cortisol was detected. The majority of the intervals produced were normally distributed with the exceptions of UA, phosphorus, and CK. Pearson correlation tests found several significant (P = <0.05) correlations between variables. The majority of the data displayed a normal distribution, unlike the previous study, with a greater number of replicates. The total protein, glucose, UA, calcium, and AST values generated were similar to those reported in the previous study. Conversely several variables such as phosphorus, CK, and albumin were not consistent with those previously reported. Evidence is presented for a lack of albumin, CK, and AST in Arachnida and thus previous data for these proteins is likely to be artifactual.

Automating Multiple Software Packages in Simulation Research for Structural Equation Modeling and Hierarchical Linear Modeling

Simulation researchers are sometimes faced with the need to use multiple statistical software packages in the process of conducting their research, potentially having to go between software packages manually. This can be a tedious and time-consuming process that generally motivates researchers to use fewer replications in their simulations than they might have used had the entire process been automated. This article describes a process by which multiple software packages can be used by governing the study with SAS and having SAS call DOS to run other software. Because this automation process should greatly reduce the time necessary for the simulations, it is hoped that this will enable researchers to use a greater number of replications and thereby enhance the precision and accuracy of their results.

Bootstrapping to investigate the effect of number of macroinvertebrate samples on confidence limits of the mean

A resampling technique (bootstrapping) was used to evaluate the effects of increasing sample number on the confidence limits of mean density and the mean number of taxa (Families) in addition to the performance of four different sampling devices used to collect macroinvertebrates in three streams of contrasting anthropogenic impact. The four sampling devices were a Hess sampler, a modified Hess sampler equipped with an internal water pump, a Surber sampler, and a two-pole kick-net. In general, confidence limits decreased predictably as the number of samples increased, most notably with the addition of a third sample. The density of organisms captured with the Surber sampler was significantly lower than that of the Hess sampler but greater than that of the kick-net sampler. No significant difference in the number of Families was found among sampling devices. Based upon a minimal 10% reduction in confidence limits compared to the previous sample, a minimum of four replicates was suggested when using the Surber sampler. In general, other methods required a greater number of replicates that the Surber to adequately represent density, but this did not hold when applied to the number of taxa. Despite the inconvenience of having to bend down to use the Surber sampler, this study found no evidence to reject its apparent popularity as a sampling method for macroinvertebrates.

Efficiency of Indirect Selection for Dry Matter Yield Based on Fresh Matter Yield in Perennial Ryegrass Sward Plots

Forage dry matter yield (DMY) is a high‐priority trait in breeding perennial ryegrass (Lolium perenne L.). However, determining dry matter concentration is highly labor intensive. For a similar level of resources, indirect selection based on fresh matter yield (FMY) would allow a greater number of replicates, genotypes, or both to be evaluated. Our objective was to estimate the efficiency of indirect selection for DMY based on FMY of pure perennial ryegrass sward plots. Over a 14‐yr period, replicated trials, containing perennial ryegrass genotypes of similar ploidy and maturity category, were sown in Ireland and assessed for DMY and FMY at each harvest over two consecutive years. Forage was generally surface dry when harvested. The estimated efficiency of indirect selection based on two replicates and comparable selection intensity was high (≥0.80). Simulation models indicated that resources would be used more efficiently by evaluating more genotypes than by increasing the number of replicates. For example, doubling the number of plots to increase the number of replicates from two to four indicated an increase in the efficiency of indirect selection from a mean 0.88 to 0.94. However, doubling the number of plots and including more genotypes, facilitating greater selection intensity, indicated an increase in the efficiency of indirect selection from a mean 0.88 to 1.04. This study indicates that FMY can be used successfully as an indirect selection method of increasing DMY in perennial ryegrass swards.

Accounting for Mode of Speciation Increases Power and Realism of Tests of Phylogenetic Asymmetry.

Tree symmetry is crucial to the investigation of evolutionary processes, particularly adaptive radiation. Testing a phylogeny for asymmetry requires a null model; the most accepted to date is the Markov (random branching) model, which assumes that speciation is instantaneous and that all species have an equal and independent chance of speciation. Such assumptions result in a high probability of asymmetric trees (which makes tests of asymmetry weak) and may be unrealistic. Subsequent modification of this model incorporated parameters conforming to diversification by peripheral-isolates speciation, producing trees that were more symmetric than those generated under the Markov model. Our reanalysis of these data, and remodeling with a greater number of replicates, shows that differences between the original Markov and modified models may have been exaggerated: different measures show that initial increases in tree symmetry under peripheral-isolates speciation are transient; symmetry on small scales actually decreases when the process of speciation requires a significant fraction of the average time between speciation events. The peripheral-isolates mode of speciation is compared with a vicariant mode, which shows steadily increasing symmetry on all scales. In cases where vicariant speciation has been common, use of a vicariant-based null model in tests of phylogenetic asymmetry is appropriate and will provide greater statistical power.

Numerical aspects of a likelihood ratio test statistic for cointegrating rank

This paper concerns numerical aspects of the distributions for the likelihood ratio test statistics for cointegrating rank. These statistics, the trace and the lambda max, play a central part in the maximum likelihood approach to multivariate cointegrating analysis. Their limit distributions are of unit root, or Dickey-Fuller type, and can be represented by functionals of Brownian motions. As of yet, one must in practice rely on simulated critical values. In this paper we investigate how the sample size and the number of replications in the simulations affect the critical values obtained. Moreover, a numerical Markov chain method for obtaining critical values in the univariate case is suggested. Results from the two approaches are compared. Finally, we present new tables of critical values based on a greater number of replications than presently is available.

Identification of Multiple‐input Transfer‐function Noise Models: A Regression Approach — Part II: Results and Conclusions

Evaluates an identification strategy, based on ridge regression, for multiple‐input models. The models are essentially the same as those of Edlund, but a far greater number of replications, 1,000, is used in each of the 21 cases tested. Furthermore, users actually identified and estimated ARIMA models of the residuals in the identification procedure of impulse response weights, unlike Edlund, who used only theoretical noise models in filtering the input and output series. A short discussion of the underlying theory was presented in Part I, Kybernetes, Vol. 22 No. 4, 1993, pp. 47–53. In Part II the procedures and results of the empirical testing are published together with some concluding remarks.

Identification of Multiple‐input Transfer‐function Noise Models: A Regression Approach — Part I: Theory

Evaluates an identification strategy, based on ridge regression, for mutliple‐input models. The corresponding computer algorithm was implemented on a VAX–8800 computer at the Computing Centre at A˚bo Akademi. The evaluation of the ridge‐regression method was carried out by simulations of different transfer‐function noise model structures. The models are essentially the same as those of Edlund, but a far greater number of replications, 1,000, is used in each of the 21 cases tested. Furthermore, uses actually identified and estimated ARIMA models of the residuals in the identification procedure of impulse response weights, unlike Edlund, who used only theoretical noise models in filtering the input and output series. A short discussion of the underlying theory is presented in Part I. The procedures and results of the empirical testing will be published in Part II in Kybernetes, Vol. 22 No. 7, 1993.

Multiple input transfer function noise modelling in the time and frequency domain:empirical evidence from Monte Carlo simulations

In the present study we have evaluated two competing methods for estimation of the impulse response weights used in the identification of transfer function models:a time domain method involving biased regression techniques and a frequency domain method utilizing a discrete Fourier transform of the cross-covariance system of the transfer function model. The algorithms were implemented on a VAX-8800 computer at the Computing Center at Abo Akademi. The evaluation of the competing methods was carried out by simulations of different transfer function noise model structures. The models are essentially the same as those of Edlund, but we have used a far greater number of replications in the cases tested. Furthermore, we have used actually identified and estimated autoregressive integrated moving-average models of the residuals in the identification procedure of impulse response weights, in contrast with Edlund who only used theoretical noise models in filtering the input and output series. After a shot discussio...