The shape parameter of Liposomes and DNA-lipid complexes determined by viscometry utilizing small sample volumes

A minicapillary viscometer utilizing <0.5 ml of sample at a volume fraction of <0.1% is described. The calculated a/b of DPPC/DPPG multilamellar liposome was 1.14 as prolate ellipsoids and a/b of dioleoylpropyltrimethyl ammonium methylsulfate-DNA complex at a charge ratio of 4: 1 (+/-) was 3.7 as prolate ellipsoids or 4.9 as oblate ellipsoids. The deviation of shape from perfect sphere is thus expressed quantitatively in more than two significant figures. In these measurement, the necessary amount of DNA is <0.5 mg.

Small-Sample Corrections for Score Tests in Birnbaum-Saunders Regressions

In this article, we deal with the issue of performing accurate small-sample inference in the Birnbaum-Saunders regression model, which can be useful for modeling lifetime or reliability data. We derive a Bartlett-type correction for the score test and numerically compare the corrected test with the usual score test and some other competitors.

Accuracy in the measurement of fertility changes with only small sample data

Includes bibliography

Accuracy in the measurement of fertility changes with only small sample data

Includes bibliography

Improving IRT parameter estimates with small sample sizes: Evaluating the efficacy of a new data augmentation technique

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.

Consequences of small sample 0-D data collection in the transportation planning process /

Mode of access: Internet.

Tables describing small-sample properties of the mean, median, standard deviation, and other statistics in sampling from various distributions /

Mode of access: Internet.

Estimation of IRT Parameters over a Small Sample. Bootstrapping of the Item Responses

2000 Mathematics Subject Classification: 97C40.

Small sample confidence intervals for the mean of a positively skewed distribution

This thesis proposes some confidence intervals for the mean of a positively skewed distribution. The following confidence intervals are considered: Student-t, Johnson-t, median-t, mad-t, bootstrap-t, BCA, T1 , T3 and six new confidence intervals, the median bootstrap-t, mad bootstrap-t, median T1, mad T1 , median T3 and the mad T3. A simulation study has been conducted and average widths, coefficient of variation of widths, and coverage probabilities were recorded and compared across confidence intervals. To compare confidence intervals, the width and coverage probabilities were compared so that smaller widths indicated a better confidence interval when coverage probabilities were the same. Results showed that the median T1 and median T3 outperformed other confidence intervals in terms of coverage probability and the mad bootstrap-t, mad-t, and mad T3 outperformed others in terms of width. Some real life data are considered to illustrate the findings of the thesis.

 Graphitization of Small Carbonate Samples for Paleoceanographic Research at the Godwin Radiocarbon Laboratory, University of Cambridge

A new radiocarbon preparation facility was set up in 2010 at the Godwin Laboratory for Palaeoclimate Research, at the University of Cambridge. Samples are graphitized via hydrogen reduction on an iron powder catalyst before being sent to the Chrono Centre, Belfast, or the Australian National University for accelerator mass spectrometry (AMS) analysis. The experimental setup and procedure have recently been developed to investigate the potential for running small samples of foraminiferal carbonate. By analyzing background values of samples ranging from 0.04 to 0.6 mg C along with similar sized secondary standards, the setup and experimental procedures were optimized for small samples. “Background” modern 14C contamination has been minimized through careful selection of iron powder, and graphitization has been optimized through the use of “small volume” reactors, allowing samples containing as little as 0.08 mg C to be graphitized and accurately dated. Graphitization efficiency/fractionation is found not to be the main limitation on the analysis of samples smaller than 0.07 mg C, which rather depends primarily on AMS ion beam optics, suggesting further improvements in small sample analysis might yet be achieved with our methodology.

Estimation of unemployment rates in small areas of Portugal: a best linear unbiased prediction approach versus a hierarchical Bayes approach

The high level of unemployment is one of the major problems in most European countries nowadays. Hence, the demand for small area labor market statistics has rapidly increased over the past few years. The Labour Force Survey (LFS) conducted by the Portuguese Statistical Office is the main source of official statistics on the labour market at the macro level (e.g. NUTS2 and national level). However, the LFS was not designed to produce reliable statistics at the micro level (e.g. NUTS3, municipalities or further disaggregate level) due to small sample sizes. Consequently, traditional design-based estimators are not appropriate. A solution to this problem is to consider model-based estimators that "borrow information" from related areas or past samples by using auxiliary information. This paper reviews, under the model-based approach, Best Linear Unbiased Predictors and an estimator based on the posterior predictive distribution of a Hierarchical Bayesian model. The goal of this paper is to analyze the possibility to produce accurate unemployment rate statistics at micro level from the Portuguese LFS using these kinds of stimators. This paper discusses the advantages of using each approach and the viability of its implementation.