The purpose of this study was to propose and evaluate a procedure for revising an existing self-administered survey that is in need of item revision and/or scale reduction while maximizing validity and reliability. The procedure was demonstrated using the Client Evaluation of Self and Treatment (CEST; Joe, Broome, Rowan-Szal, & Simpson, 2002), a self-administered survey used in drug and alcohol treatment agencies. The procedure included confirmatory and exploratory factor analyses of a large dataset of completed CEST surveys, a readability analysis, and cognitive interviewing of two different groups of respondents to determine what problems they might have with CEST items. The cognitive interviewing revealed a number of issues that led to confusion among respondents, including items with two distinct concepts embedded, items containing absolutes and vague qualifiers, misinterpreted items, and terms and phrases respondents had difficulty understanding. The CEST was also judged to be long and potentially burdensome to respondents. Based on the results of this evaluation, a new survey—the Brief Assessment of Self in Context (BASIC)—also intended for use by substance abuse treatment providers, was constructed. First, factor analyses of the CEST and advice from an expert panel were used to determine which scales to retain. Next, quantitative analyses and cognitive interviewing helped determine which CEST items to retain and which to revise. Readability, sound item writing principles, and response format and scale requirements were also used to determine which items to include in the initial draft of the BASIC and guided item construction when needed. After the panel of experts provided feedback on the first revision, a final draft was prepared. Another round of cognitive interviewing was followed by administration of the final draft of the survey to a representative sample. The results indicated that the BASIC’s items are clear, unambiguous, and easy to interact with and understand, and that the instrument is an improvement over the CEST. In brief, the procedure demonstrated in this study produced a psychometrically sound instrument composed of items that are easy for respondents to access. / text

This thesis describes the design, maintenance and statistical analysis involved in undertaking a Longitudinal Survey. A longitudinal survey (or study) obtains observations or responses from individuals over several times over a defined period. This enables the direct study of changes in an individual's response over time. In particular, it distinguishes an individual's change over time from the baseline differences among individuals within the initial panel (or cohort). This is not possible in a cross-sectional study. As such, longitudinal surveys give correlated responses within individuals. Longitudinal studies therefore require different considerations for sample design and selection and analysis from standard cross-sectional studies. This thesis looks at the methodology for analysing social surveys. Most social surveys comprise of variables described as categorical variables. This thesis outlines the process of sample design and selection, interviewing and analysis for a longitudinal study. Emphasis is given to categorical response data typical of a survey. Included in this thesis are examples relating to the Goodna Longitudinal Survey and the Longitudinal Survey of Immigrants to Australia (LSIA). Analysis in this thesis also utilises data collected from these surveys. The Goodna Longitudinal Survey was conducted by the Queensland Office of Economic and Statistical Research (a portfolio office within Queensland Treasury) and began in 2002. It ran for two years whereby two waves of responses were collected.

Submitted by Cássia Santos (cassia.bcufg@gmail.com) on 2014-11-11T12:06:48Z No. of bitstreams: 2 Tese Geiziane Tessarolo - 2014.pdf: 5275889 bytes, checksum: fb092b496eb6eae85e89c28d423c44d9 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2014-11-17T15:10:55Z (GMT) No. of bitstreams: 2 Tese Geiziane Tessarolo - 2014.pdf: 5275889 bytes, checksum: fb092b496eb6eae85e89c28d423c44d9 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-11-17T15:10:55Z (GMT). No. of bitstreams: 2 Tese Geiziane Tessarolo - 2014.pdf: 5275889 bytes, checksum: fb092b496eb6eae85e89c28d423c44d9 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-04-29 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Aim Species Distribution Models (SDM) can be used to predict the location of unknown populations from known species occurrences. It follows that how the data used to calibrate the models are collected can have a great impact on prediction success. We evaluated the influence of different survey designs and their interaction with the modelling technique on SDM performance. Location Iberian Peninsula Methods We examine how data recorded using seven alternative survey designs (random, systematic, environmentally stratified by class and environmentally stratified using p-median, biased due to accessibility, biased by human density aggregation and biased towards protected areas) could affect SDM predictions generated with nine modelling techniques (BIOCLIM, Gower distance, Mahalanobis distance, Euclidean distance, GLM, MaxEnt, ENFA and Random Forest). We also study how sample size, species’ characteristics and modelling technique affected SDM predictive ability, using six evaluation metrics. Results Survey design has a small effect on prediction success. Characteristics of species’ ranges rank highest among the factors affecting SDM results: the species with lower relative occurrence area (ROA) are predicted better. Model predictions are also improved when sample size is large. Main conclusions The species modelled – particularly the extent of its distribution – are the largest source of influence over SDM results. The environmental coverage of the surveys is more important than the spatial structure of the calibration data. Therefore, climatic biases in the data should be identified to avoid erroneous conclusions about the geographic patterns of species distributions. / Aim Species Distribution Models (SDM) can be used to predict the location of unknown populations from known species occurrences. It follows that how the data used to calibrate the models are collected can have a great impact on prediction success. We evaluated the influence of different survey designs and their interaction with the modelling technique on SDM performance. Location Iberian Peninsula Methods We examine how data recorded using seven alternative survey designs (random, systematic, environmentally stratified by class and environmentally stratified using p-median, biased due to accessibility, biased by human density aggregation and biased towards protected areas) could affect SDM predictions generated with nine modelling techniques (BIOCLIM, Gower distance, Mahalanobis distance, Euclidean distance, GLM, MaxEnt, ENFA and Random Forest). We also study how sample size, species’ characteristics and modelling technique affected SDM predictive ability, using six evaluation metrics. Results Survey design has a small effect on prediction success. Characteristics of species’ ranges rank highest among the factors affecting SDM results: the species with lower relative occurrence area (ROA) are predicted better. Model predictions are also improved when sample size is large. Main conclusions The species modelled – particularly the extent of its distribution – are the largest source of influence over SDM results. The environmental coverage of the surveys is more important than the spatial structure of the calibration data. Therefore, climatic biases in the data should be identified to avoid erroneous conclusions about the geographic patterns of species distributions.

Even with clear advantages to using internet based survey research, there are still some uncertainties to which survey methods are most conducive to an online platform. Most survey method literature, whether focusing on online, telephone, or in-person formats, tend to observe little to no differences between using various survey modes and survey results. Despite this, there is little research focused on the interaction effect between survey formatting, in terms of design and framing, and public opinion on social issues, specifically child immigration policies - a recent topic of popular debate. This paper examines an anomalous result found within the 2016 Cooperative Congressional Election Study (CCES) public opinion immigration question focusing on a DACA-related policy, where support was evenly split on the typically highly favored policy. To decipher the unprecedented result, an experimental survey design was conducted via Qualtrics by comparing various survey formats (single-style, forced choice, Likert scale) and inclusionary policy details to the original CCES “select all that apply” matrix style. By comparing the experimental polls, the results indicated that the “select all that apply” matrix again produced anomalous results, while the various other methods produced a breakdown similar to typical DACA-related polling data. These findings have necessary implications for future survey designs and those examining public opinion on child immigration policies.

<div>The purpose of this research was to develop and validate an instrument designed to assess programming of youth development organizations. The instrument can be used by leaders of youth development organizations to monitor the organization’s performance in developing productive and engaged citizens. This research viewed youth development organizations as a microsystem that youth interact with (Bronfenbrenner & Morris, 2006). A complete review of the literature on youth development organizations was conducted to determine the components of positive youth development organizations. The resulting conceptual framework consisted of project, skills and knowledge, community contribution, high-density experiences, environment, non-parental adult, and near-peer role models.</div><div><br></div><div>An item pool was developed based on the literature available on youth development organization programming. This item pool was reviewed by experts in youth development organization programming and inclusion. Then the items were entered into two tools to assess grammar and concise language. Third, the items were administered to a small sample then analyzed for correlations and contributions to reliability. Items were eliminated if they correlated too highly with other items and if they did not contribute to the reliability of the scale. Fourth, the items were administered to a broader sample and correlations and reliability measures were analyzed again with more items removed. Finally, the items were administered to another sample and analyzed for multicollinearity and reliability. The final sample took the survey a second time and responses were compared based on paired t-tests to establish test-retest reliability.<br></div><div><br></div><div>The 15-item instrument exhibits appropriate measures of validity and reliability to recommend its usage by youth development organization leaders to evaluation programming. The instrument is parsimonious so leaders can add program-specific questions while avoiding participant fatigue. A complete version of the instrument is available in the appendices.</div>

Web-based learning has become an important component of education. Higher education institutions in Thailand have become increasingly aware of the widespread use and effectiveness of web-based learning systems. However, the adoption of such learning systems is growing at a slow pace in Thailand. The purpose of this study was to test the Unified Theory of Acceptance and Use of Technology (UTAUT), that performance expectancy, effort expectancy, social influence, and facilitating conditions have a positive effect on usage intention and adoption of web-based learning systems by instructors, in the Departments of Education at the Rajabhat Universities, Thailand; and to test whether experience of use, age, and gender have moderating effects in the adoption of web-based learning systems there. The research design used in this study was a cross-sectional survey design. Data were collected by means of a self-administered paper questionnaire. The study was conducted among the instructors in the departments of education at the Rajabhat Universities in Thailand. A total of 725 surveys were sent out, 454 questionnaires were returned by the respondents, and 14 were eliminated as outliers; thus, the final data set for the study was 440 samples. The two-step approach of SEM was used to test the model and the study's hypotheses; first, the measurement model was measured to examine the validity and reliability of the data; next, the structural model was measured to test the hypotheses of the study and the fitness of the data to the model. The results of this study revealed several factors that can affect instructors’ adoption of a web-based learning system and which can enhance the web-based learning performance of instructors in the Rajabhat Universities and throughout higher education in Thailand.