Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

Understanding long-term hunting statistics: the case of Spain (1972-2007)

Hunting is assuming a growing role in the current European forestry and agroforestry landscape. However, consistent statistical sources that provide quantitative information for policy-making, planning and management of game resources are often lacking. In addition, in many instances statistical information can be used without sufficient evaluation or criticism. Recently, the European Commission has declared the importance of high quality hunting statistics and the need to set up a common scheme in Europe for their collection, interpretation and proper use. This work aims to contribute to this current debate on hunting statistics in Europe by exploring data from the last 35 years of Spanish hunting statistics. The analysis focuses on the three major pillars underpinning hunting activity: hunters, hunting grounds and game animals. First, the study aims to provide a better understanding of official hunting statistics for use by researchers, game managers and other potential users. Second, the study highlights the major strengths and weaknesses of the statistical information that was collected. The results of the analysis indicate that official hunting statistics can be incomplete, dispersed and not always homogeneous over a long period of time. This is an issue of which one should be aware when using official hunting data for scientific or technical work. To improve statistical deficiencies associated with hunting data in Spain, our main suggestion is the adoption of a common protocol on data collection to which different regions agree. This protocol should be in accordance with future European hunting statistics and based on robust and well-informed data collection methods. Also it should expand the range of biological, ecological and economic concepts currently included to take account of the profound transformations experienced by the hunting sector in recent years. As much as possible, any future changes in the selection of hunting statistics should allow for comparisons between new variables with the previous ones.

Development of a tool for designing tests based on statistics and metadata

Background: This project’s idea arose derived of the need of the professors of the department “Computer Languages and Systems and Software Engineering (DLSIIS)” to develop exams with multiple choice questions in a more productive and comfortable way than the one they are currently using. The goal of this project is to develop an application that can be easily used by the professors of the DLSIIS when they need to create a new exam. The main problems of the previous creation process were the difficulty in searching for a question that meets some specific conditions in the previous exam files; and the difficulty for editing exams because of the format of the employed text files. Result: The results shown in this document allow the reader to understand how the final application works and how it addresses successfully every customer need. The elements that will help the reader to understand the application are the structure of the application, the design of the different components, diagrams that show the workflow of the application and some selected fragments of code. Conclusions: The goals stated in the application requirements are finally met. In addition, there are some thoughts about the work performed during the development of the application and how it improved the author skills in web development.

Expression of multiple insulin and insulin-like growth factor receptor genes in salmon gill cartilage

In mammals, one of the major actions of insulin-like growth factor I (IGF-I) is to increase skeletal growth by stimulating new cartilage formation. IGF-I stimulates chondrocytes in vitro to synthesize new cartilage matrix, measured by enhanced uptake of 35S-sulfate, but the addition of insulin does not produce a similar effect except when added at high concentrations. However, recent studies have shown that, in teleosts, both insulin and IGF-I are potent activators of 35S-sulfate uptake in gill cartilage. To further characterize the growth-promoting activities of these hormones in fish, we have used reverse transcriptase-linked PCR to analyze the expression of insulin receptor family genes in salmon gill cartilage. Partial cDNA sequences encoding the tyrosine kinase domains from six distinct members of the IR gene family were obtained, and sequence comparisons revealed that four of the cDNAs encoded amino acid sequences that were highly homologous to human IR whereas the encoded sequences from two of the cDNAs were more similar to the human type I IGF receptor (IGF-R). Furthermore, a comparative reverse transcriptase-linked PCR assay revealed that the four putative IR mRNAs expressed in toto in gill cartilage were 56% of that found in liver whereas the expressed amount of the two IGF-R mRNAs was 9-fold higher compared with liver. These results suggest that the chondrogenic actions of insulin and IGF-I in fish are mediated by the ligands binding to their cognate receptors. However, further studies will be required to characterize the binding properties and relative contribution of the individual IR and IGF-R genes.

Nonclassical light revealed by the joint statistics of simultaneous measurements

Nonclassicality cannot be a single-observable property, since the statistics of any quantum observable is compatible with classical physics. We develop a general procedure to reveal nonclassical behavior of light states from the joint statistics arising in the practical measurement of multiple observables. Beside embracing previous approaches, this protocol can disclose nonclassical features for standard examples of classical-like behavior, such as SU(2) and Glauber coherent states. When combined with other criteria, this would imply that every light state is nonclassical.

Annual mileage comparisons and accident and injury rates by make, model. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Comparisons of accident data from Western New York, New York State, and the United States. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Energy use and other comparisons between diesel and gasoline pickup trucks. Interim report.

Transportation Systems Center, Cambridge, Mass.

Use of multiple regression analysis to summarize and interpret linear programming shadow prices in an economic planning model /

Issued May 1980.

Report of the Committee on Evaluation of Wage Data for Interarea Comparisons : Miami, Florida, June 17, 1964.

Cover title.

Maintaining and updating semantic context in schizophrenia: an investigation of the effects of multiple remote primes

Conflicting findings regarding the ability of people with schizophrenia to maintain and update semantic contexts have been due, arguably, to vagaries within the experimental design employed (e.g. whether strongly or remotely associated prime-target pairs have been used, what delay between the prime and the target was employed, and what proportion of related prime-target pairs appeared) or to characteristics of the participant cohort (e.g. medication status, chronicity of illness). The aim of the present study was to examine how people with schizophrenia maintain and update contextual information over an extended temporal window by using multiple primes that were either remotely associated or unrelated to the target. Fourteen participants with schizophrenia and 12 healthy matched controls were compared across two stimulus onset asynchronies (SOAs) (short and long) and two relatedness proportions (RP) (high and low) in a crossed design. Analysis of variance statistics revealed significant two- and three-way interactions between Group and SOA, Group and Condition, SOA and RP, and Group, SOA and RP. The participants with schizophrenia showed evidence of enhanced remote priming at the short SOA and low RP, combined with a reduction in the time course over which context could be maintained. There was some sensitivity to biasing contextual information at the short SOA, although the mechanism over which context served to update information appeared to be different from that in the controls. The participants with schizophrenia showed marked performance decrements at the long SOA (both low and high RP). Indices of remote priming at the short (but not the long) SOA correlated with both clinical ratings of thought disorder and with increasing length of illness. The results support and extend the hypothesis that schizophrenia is associated with concurrent increases in tonic dopamine activity and decreases in phasic dopamine activity. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Multiple imputation for body mass index: lessons from the Australian Longitudinal Study on Women's Health

In large epidemiological studies missing data can be a problem, especially if information is sought on a sensitive topic or when a composite measure is calculated from several variables each affected by missing values. Multiple imputation is the method of choice for 'filling in' missing data based on associations among variables. Using an example about body mass index from the Australian Longitudinal Study on Women's Health, we identify a subset of variables that are particularly useful for imputing values for the target variables. Then we illustrate two uses of multiple imputation. The first is to examine and correct for bias when data are not missing completely at random. The second is to impute missing values for an important covariate; in this case omission from the imputation process of variables to be used in the analysis may introduce bias. We conclude with several recommendations for handling issues of missing data. Copyright (C) 2004 John Wiley Sons, Ltd.

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulae for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.

Comparative phylogeographic summary statistics for testing simultaneous vicariance

Testing for simultaneous vicariance across comparative phylogeographic data sets is a notoriously difficult problem hindered by mutational variance, the coalescent variance, and variability across pairs of sister taxa in parameters that affect genetic divergence. We simulate vicariance to characterize the behaviour of several commonly used summary statistics across a range of divergence times, and to characterize this behaviour in comparative phylogeographic datasets having multiple taxon-pairs. We found Tajima's D to be relatively uncorrelated with other summary statistics across divergence times, and using simple hypothesis testing of simultaneous vicariance given variable population sizes, we counter-intuitively found that the variance across taxon pairs in Nei and Li's net nucleotide divergence (pi(net)), a common measure of population divergence, is often inferior to using the variance in Tajima's D across taxon pairs as a test statistic to distinguish ancient simultaneous vicariance from variable vicariance histories. The opposite and more intuitive pattern is found for testing more recent simultaneous vicariance, and overall we found that depending on the timing of vicariance, one of these two test statistics can achieve high statistical power for rejecting simultaneous vicariance, given a reasonable number of intron loci (> 5 loci, 400 bp) and a range of conditions. These results suggest that components of these two composite summary statistics should be used in future simulation-based methods which can simultaneously use a pool of summary statistics to test comparative the phylogeographic hypotheses we consider here.