As men and women return from serving on the frontlines of Operations Enduring Freedom (OEF; Afghanistan) and Iraqi Freedom (OIF; Iraq), many struggle with emotional or behavioral difficulties stemming from the stresses of battle. However, research has shown that these service members may be unwilling or unable to recognize or report such difficulties due to such factors as amnesia, avoidance, or cognitive impairment. Hence, the burden to recognize distress and encourage treatment increasingly falls on peers, friends, and especially intimate partners. Given that this responsibility is often placed on significant others, it is imperative to determine which symptoms are amenable to detection by informants and which are not. The current study examined the ability of female spouses of Vietnam veterans to report on various indicators of posttraumatic stress disorder (PTSD) using the Mississippi Scale for Combat-Related PTSD. Item response theory (IRT) analyses were conducted with a dataset composed of both self- and informant reports using the same items regarding the same individual in order to examine the item-level properties. Results from these analyses indicated that the ability of both spouses and veterans to detect PTSD symptoms varies across item content and that items themselves do not relate equally to, or become diagnostic at the same level of, PTSD. Overall, veterans showed greater sensitivity to their own symptoms and were able to provide more information than their spouses for nearly every item rated by independent experts to be overt or covert. However, some items provided greater information when endorsed by the spouse versus the veteran even though, consistent with the majority of other items, these items were endorsed by the spouse only once the PTSD symptoms had reached greater severity. Implications of these findings as well as future directions for research regarding observer reports of PTSD symptomatology were explored.

A novel method by which to calculate the near edge X-rayabsorption fine structure region of the X-ray absorption spectrum has been derived and implemented. By means of damped coupled cluster theory at coupled cluster levels CCS, CC2, CCSD and CCSDR(3), the spectra of neon and methane have been investigated. Using methods incorprating double excitations, the important relaxation effects maybe taken into account by simultaneous excitation of the core electron and relaxation of other electrons. An asymmetric Lanczos-chain driven approach has been utilized as a means to partially resolve the excitation space given by the coupled cluster Jacobian. The K-edge of the systems have been considered, and relativistic effects are estimated with use of the Douglas--Kroll scalar relativistic Hamiltonian. Comparisons have been made to results obtained with the four-component static-exchange approach and ionization potentials obtained by the {Delta}SCF-method. The appropriate basis sets by which to describe the core and excited states have been been determined.  The addition of core-polarizing functions and diffuse or Rydberg functions is important for this description. Scalar relativistic effects accounts for an increase in excitation energies due to the contraction of the 1s-orbital, and this increase is seen to be 0.88 eV for neon. The coupled cluster hierachy shows a trend of convergence towards the experimental spectrum, with an 1s -> 3p excitation energy for neon of an accuracy of 0.40 eV at a relativistic CCSDR(3) level of theory. Results obtained at the damped coupled cluster and STEX levels of theory, respectively, are seen to be in agreement, with a mere relative energy shift.

Information Systems (IS) research frequently uses survey data to measure the interplay between technological systems and human beings. Researchers have developed sophisticated procedures to build and validate multi-item scales that measure real world phenomena (latent constructs). Most studies use the so-called classical test theory (CTT), which suffers from several shortcomings. We first compare CTT to Item Response Theory (IRT) and subsequently apply a Rasch model approach to measure hedonic aspects of websites. The results not only show which attributes are best suited for scaling hedonic information systems, but also introduce IRT as a viable substitute that overcomes severall shortcomings of CTT. (author´s abstract) / Series: Research Report Series / Department of Statistics and Mathematics

<p>This dissertation is devoted to modeling complex data from the</p><p>Bayesian perspective via constructing priors with latent structures.</p><p>There are three major contexts in which this is done -- strategies for</p><p>the analysis of dynamic longitudinal data, estimating</p><p>shape-constrained functions, and identifying subgroups. The</p><p>methodology is illustrated in three different</p><p>interdisciplinary contexts: (1) adaptive measurement testing in</p><p>education; (2) emulation of computer models for vehicle crashworthiness; and (3) subgroup analyses based on biomarkers.</p><p>Chapter 1 presents an overview of the utilized latent structured</p><p>priors and an overview of the remainder of the thesis. Chapter 2 is</p><p>motivated by the problem of analyzing dichotomous longitudinal data</p><p>observed at variable and irregular time points for adaptive</p><p>measurement testing in education. One of its main contributions lies</p><p>in developing a new class of Dynamic Item Response (DIR) models via</p><p>specifying a novel dynamic structure on the prior of the latent</p><p>trait. The Bayesian inference for DIR models is undertaken, which</p><p>permits borrowing strength from different individuals, allows the</p><p>retrospective analysis of an individual's changing ability, and</p><p>allows for online prediction of one's ability changes. Proof of</p><p>posterior propriety is presented, ensuring that the objective</p><p>Bayesian analysis is rigorous.</p><p>Chapter 3 deals with nonparametric function estimation under</p><p>shape constraints, such as monotonicity, convexity or concavity. A</p><p>motivating illustration is to generate an emulator to approximate a computer</p><p>model for vehicle crashworthiness. Although Gaussian processes are</p><p>very flexible and widely used in function estimation, they are not</p><p>naturally amenable to incorporation of such constraints. Gaussian</p><p>processes with the squared exponential correlation function have the</p><p>interesting property that their derivative processes are also</p><p>Gaussian processes and are jointly Gaussian processes with the</p><p>original Gaussian process. This allows one to impose shape constraints</p><p>through the derivative process. Two alternative ways of incorporating derivative</p><p>information into Gaussian processes priors are proposed, with one</p><p>focusing on scenarios (important in emulation of computer</p><p>models) in which the function may have flat regions.</p><p>Chapter 4 introduces a Bayesian method to control for multiplicity</p><p>in subgroup analyses through tree-based models that limit the</p><p>subgroups under consideration to those that are a priori plausible.</p><p>Once the prior modeling of the tree is accomplished, each tree will</p><p>yield a statistical model; Bayesian model selection analyses then</p><p>complete the statistical computation for any quantity of interest,</p><p>resulting in multiplicity-controlled inferences. This research is</p><p>motivated by a problem of biomarker and subgroup identification to</p><p>develop tailored therapeutics. Chapter 5 presents conclusions and</p><p>some directions for future research.</p> / Dissertation

The application of diagnostic thresholds plays an important role in the classification of mental disorders. Despite their importance, many diagnostic thresholds are set arbitrarily, without much empirical support. This paper seeks to introduce and analyze a new empirically based way of setting diagnostic thresholds for a category of mental disorders that has historically had arbitrary thresholds, the personality disorders (PDs). I analyzed data from over 2,000 participants that were part of the Methods to Improve Diagnostic Assessment and Services (MIDAS) database. Results revealed that functional outcome scores, as measured by Global Assessment of Functioning (GAF) scores, could be used to identify diagnostic thresholds and that the optimal thresholds varied somewhat by personality disorder (PD) along the spectrum of latent severity. Using the Item response theory (IRT)-based approach, the optimal threshold along the spectrum of latent severity for the different PDs ranged from θ = 1.50 to 2.25. Effect sizes using the IRT-based approach ranged from .34 to 1.55. These findings suggest that linking diagnostic thresholds to functional outcomes and thereby making them less arbitrary is an achievable goal. This study has introduced a new and uncomplicated way to empirically set diagnostic thresholds while also taking into consideration that items within diagnostic sets may function differently. Although purely an initial demonstration meant only to serve as an example, by using this approach, there exists the potential that diagnostic thresholds for all disorders could one day be set on an empirical basis.

Cognitive Diagnostic Models (CDMs) are a useful way to identify potential areas of intervention for students who may not have mastered various skills and abilities at the same time as their peers. Traditionally, CDMs have been used on narrowly defined classroom tests, such as those for determining whether students are able to use different algebraic principles correctly. In the current study, the Deterministic Input, Noisy "And" Gate model (DINA; Haertel, 1989; Junker&Sijtsma, 2001) and the Compensatory Reparameterized Unified Model (CRUM; Hartz, 2002), as parameterized by the log-linear cognitive diagnosis model (LCDM; Henson, Templin,&Willse, 2009), were used to analyze the utility of pre-defined cognitive components in estimating students' abilities in a broadly defined, standardized mathematics achievement test. The attribute mastery profile distributions were compared; the majority of students was classified into the extremes of no mastery or complete mastery for both the CRUM and DINA models, though greater variability among attribute mastery classifications was obtained by the CRUM.

<p>Reading and understanding literature does not necessarily have to be an individual act. The aim of this essay is to investigate what happens when six students read a text by Kazuo Ishiguro A Family Supper and then discuss it in a communicative situation. The essay bases its ideas on the sociocultural theory and the reader-response theory. The sociocultural perspective argues that people develop and progress during social interaction, moreover by communicating with other people and by being inspired and subsequently educated through taking part in different social contexts. My idea with this essay is to observe a literary discussion in a group. The observation emphasizes both the individual contribution to the literary discussion and the function of the group. By analyzing the participation of the individual students, I reached the conclusion that the students deal with literature in many different ways. Some focus only on the text and the plot, others discuss social issues in connection to the text and some only respond to the others’ arguments. When studying the group, I looked at the balance in the group, the turn taking between the members and the level of participation. The reader-response theory bases its idea on the reader and the text and the fact that they are connected in a mutual transaction. Every reader brings his or her experiences to the understanding of the text and thereby a text can have multiple alternative interpretations considering the amount of readers. The analysis section in this essay consists of several parts, such as an individual reflection, a group discussion and an individual evaluation.</p>

This study investigated the efficacy of the lz person fit statistic for detecting aberrant responding with unidimensional pairwise preference (UPP) measures, constructed and scored based on the Zinnes-Griggs (ZG, 1974) IRT model, which has been used for a variety of recent noncognitive testing applications. Because UPP measures are used to collect both "self-" and "other-" reports, I explored the capability of lz to detect two of the most common and potentially detrimental response sets, namely fake good and random responding. The effectiveness of lz was studied using empirical and theoretical critical values for classification, along with test length, test information, the type of statement parameters, and the percentage of items answered aberrantly (20%, 50%, 100%). We found that lz was ineffective in detecting fake good responding, with power approaching zero in the 100% aberrance conditions. However, lz was highly effective in detecting random responding, with power approaching 1.0 in long-test, high information conditions, and there was no diminution in efficacy when using marginal maximum likelihood estimates of statement parameters in place of the true values. Although using empirical critical values for classification provided slightly higher power and more accurate Type I error rates, theoretical critical values, corresponding to a standard normal distribution, provided nearly as good results.

One of the cornerstones of the R system for statistical computing is the multitude of packages contributed by numerous package authors. This makes an extremely broad range of statistical techniques and other quantitative methods freely available. So far no empirical study has investigated psychological factors that drive authors to participate in the R project. This article presents a study of R package authors, collecting data on different types of participation (number of packages, participation in mailing lists, participation in conferences), three psychological scales (types of motivation, psychological values, and work design characteristics), as well as various sociodemographic factors. The data are analyzed using item response models and subsequent generalized linear models, showing that the most important determinants for participation are a hybrid form of motivation and the social characteristics of the work design. Other factors are found to have less impact or influence only specific aspects of participation. (authors' abstract)

This simulation study compared the performance of two multilevel measurement testlet (MMMT) models: Beretvas and Walker’s (2008) two-level MMMT model and Jiao, Wang, and Kamata’s (2005) three-level model. Several conditions were manipulated (including testlet length, sample size, and the pattern of the testlet effects) to assess the impact on the estimation of fixed and random effect parameters. While testlets, in which items share the same stimulus, are common in educational tests, testlet item scores violate the assumption of local item independence (LID) underlying item response theory (IRT). Modeling LID has been widely discussed in previous studies (for example, Bradlow, Wainer, and Wang, 1999; Wang, Bradlow, and Wainer, 2002; Wang, Cheng, and Wilson, 2005). More recently, Jiao et al. (2005) proposed a three-level MMMT (MMMT-3r) in which items are modeled as nested within testlets (level two) and then testlets are nested with persons (level three). Testlet effects are typically modeled as random in previous studies involving LID. However, item effects (difficulties) are commonly modeled as fixed under IRT models: that is, persons with the same ability level are assumed to have the same probability of answering an item correctly. Therefore, it is also important that a testlet effects model permit modeling of item effects as fixed. Moreover, modeling testlet effect as random implies testlets are being sampled from a larger population of testlets. However, as with item effects, researchers are typically more interested in a particular set of items or testlets that are being used in an assessment. Given the interest of the researcher or psychometrician using a testlet response model, it seems more useful to use a testlet response model that permits modeling testlets effects as fixed. An alternative MMMT that permits modeling testlet effect as fixed and/or randomly varying has been proposed (Beretvas and Walker, 2008). The MMMT-2f and MMMT-2r models treat testlet effects as item-set-specific but not person-specific. However, no simulation has been conducted to assess how this proposed model performs. The current study compared the performance of the MMMT-2f, MMMT-2r with that of the MMMT-3r. Results of the present simulation study showed that the MMMT-2r yielded the best parameter bias in estimation on fixed item effects, fixed testlet effects, and random testlet effects for conditions with nonzero equal pattern of random testlet effects’ variance even when the MMMMT-2r was not the generating model. However, random effects estimation did not perform well when unequal random testlet effects’ variances were generated. Fit indices did not perform well either as other studies have found. And it should be emphasized that model differences were of very little practical significance. From a modeling perspective, MMMT-2r does allow the greatest flexibility in terms of modeling testlet effects as fixed, random, or both. / text