Search results

In this chapter, we review four methods for identifying function and addressing function in intervention. These include functional analysis, the Functional-Assessment-Based Intervention (FABI) Model, the Competing Pathways Model, and the Prevent-Teach-Reinforce Model. For each, we describe the methods and procedures used to identify function and design intervention support, briefly review supporting evidence, and identify the advantages and limitations associated with each approach.

Treatment integrity (TI; also known as fidelity of implementation, treatment fidelity, and procedural reliability) refers to the degree to which an intervention is implemented as intended. TI data provides evidence of the internal validity of a study; without TI data, one cannot attribute observed effects to an intervention or distinguish whether interventions that fail do so because of problems with the intervention, its delivery, or both. Unfortunately, the field of intervention research has seen limited progress in the assessment and reporting of TI over time. This chapter describes the development of models of TI across fields, options for measuring TI, and important issues yet to be resolved.

Secondary-level students with emotional and behavioral disorders (EBD) have significant academic and behavioral difficulties that require expert instruction to improve school and transition outcomes. Tensions between free and appropriate public education (FAPE) and least restrictive environment (LRE) mandates occur in the planning and delivery of specialized instruction and supports to these students. In this chapter, we consider alternate conceptions of freedoms as they may relate to the provision of special education services. However, a recent Supreme Court ruling highlighted the importance of FAPE in consideration of the student’s individual circumstances. This emphasis on FAPE poses a significant challenge for teachers, who may be unprepared and insufficiently supported to be effective. As a result, it may be advantageous to organize effective practices according to a taxonomy that is based on the types of performance demands that are placed on students in secondary classrooms. The taxonomy we propose provides a framework to support teacher training and decision making. We provide an overview of the performance demands placed upon students with EBD in secondary grades. Examples of effective practices to improve student performance for each type of demand are provided.

In this study, the authors investigate methods of sequential analysis to test prospectively for the existence of a unit root against stationary or explosive states in a p-th order autoregressive (AR) process monitored over time. Our sequential sampling schemes use stopping times based on the observed Fisher information of a local-to-unity parameter. In contrast to the Dickey–Fuller (DF) test statistic, the sequential test statistic has asymptotic normality. The authors derive the joint limit of the test statistic and the stopping time, which can be characterized using a 3/2-dimensional Bessel process driven by a time-changed Brownian motion. The authors obtain their limiting joint Laplace transform and density function under the null and local alternatives. In addition, simulations are conducted to show that the theoretical results are valid.

This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial condition. The new estimators we introduce are weighted averages of the well-known first difference (FD) GMM/IV estimator and the pooled ordinary least squares (POLS) estimator. The proposed procedure seeks to exploit the differing strengths of the FD GMM/IV estimator relative to the pooled OLS estimator. In particular, the latter is inconsistent in the stationary case but is consistent and asymptotically normal with a faster rate of convergence than the former when the underlying panel autoregressive process has a unit root. By averaging the two estimators in an appropriate way, we are able to construct a class of estimators which are consistent and asymptotically standard normal, when suitably standardized, in both the stationary and the unit root case. The results of our simulation study also show that our proposed estimator has favorable finite sample properties when compared to a number of existing estimators.

This chapter proposes a nonparametric estimator of the risk neutral density (RND) based on cross-sectional European option prices. The authors recast the arbitrage-free equation for option pricing as a functional linear regression model where the regressor is a curve and the independent variable is a scalar corresponding to the option price. Then, the authors show that the RND can be viewed as the solution of an ill-posed integral equation. To estimate the RND, the authors use an iterative method called Landweber-Fridman (LF). Then, the authors establish the consistency and asymptotic normality of the estimated RND. These results can be used to construct a confidence interval around the curve. Finally, some Monte Carlo simulations and application to the S&P 500 options show that this method performs well compared to alternative methods.

There are several ways that risks and uncertainties might be discussed in the context of assessment and analysis – several of which could be inferred from previous chapters. Here, Chapters 6 and 7 are structured around what might be called strategic risks/uncertainties and operational risks/uncertainties.

This chapter presents the strategic risk/uncertainty assessment and analysis challenge. Most current thinking on risk management – enterprise risk management (ERM), but even including more traditional approaches – place expectations on leaders and top managers to provide guidance on risk policy, but also require those individuals to understand the challenges for which they are responsible. As implied previously, this domain mainly consists of uncertainties. Typically, top managers deal with aggregated operational data that – in itself – might be measurable but owing to the effects of consolidation tend to present leaders with a singular strategy/issue that is unique to the organisation and therefore not well-suited to statistical analysis. Furthermore, scanning for future threats and opportunities is decidedly a matter of considering the unknown, the emergent, and even the unimaginable. Within this assortment of challenges are the very large-scale features that – among many things – compel consideration of collaboration with other organisations. Here these special risks/uncertainties are labelled global risks.

The issue of complexity is here revisited, and this discussion serves two particular purposes. Complexity theory (and complex adaptive systems) offers some insights into methods of assessment and analysis, but they also provide some useful views on the nature of the uncertainty field in the context of complex environments. This discussion will offer some consideration of traditional, ERM, and alternative approaches and the appropriate ‘fit’ of assessment and analysis into these frameworks.

Students with learning disabilities (LD) have a wide range of academic needs. Since the passing of P.L. 94-142, significant research has been done on effective interventions for this group of students. Starting with the Learning Disabilities Research Institutes through the recent Handbook of Learning Disabilities, reviews of lines of research make several broad ideas about interventions clear. Primary among these is that students with LD can learn if provided with appropriate, effective instruction. Specifics about this idea and its implications are discussed in the following chapter.

Transition can be seen as the capstone of many if not most efforts of special educators on behalf of students with disabilities. Transition programs must build upon the foundation set by general and special education teachers to promote accomplishments that will support engagement in adult life. The assumption underlying transition policy is that classroom personnel are adequately trained and supported to promote such outcomes. We investigated that assumption through research on the perceptions of 17 graduate students or recent completers of an alternative certification program serving a large urban district in the northeast. Study participants were interviewed regarding the provision of special education services at their assigned schools, the manner in which they were utilized, the degree to which they felt prepared and supported to teach students with disabilities, and recommendations for improving special education services, teacher training, and support. All participants taught special education students in secondary settings and were assigned to different schools. Several themes were identified including stress due to professional demands, concerns with collaboration and the quality of special education services, and a need for additional special education training. Implications for transition are discussed.