A comparison of mean phase difference and generalized least squares for analyzing single-case data

The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurements The first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

Assigning and combining probabilities in single-case studies

There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current paper proposes an approach for obtaining further numerical evidence on the importance of the results, complementing the substantive criteria, visual analysis, and primary summary measures. This additional evidence consists of obtaining the statistical significance of the outcome when referred to the corresponding sampling distribution. This sampling distribution is formed by the values of the outcomes (expressed as data nonoverlap, R-squared, etc.) in case the intervention is ineffective. The approach proposed here is intended to offer the outcome"s probability of being as extreme when there is no treatment effect without the need for some assumptions that cannot be checked with guarantees. Following this approach, researchers would compare their outcomes to reference values rather than constructing the sampling distributions themselves. The integration of single-case studies is problematic, when different metrics are used across primary studies and not all raw data are available. Via the approach for assigning p values it is possible to combine the results of similar studies regardless of the primary effect size indicator. The alternatives for combining probabilities are discussed in the context of single-case studies pointing out two potentially useful methods one based on a weighted average and the other on the binomial test.

Regression-based techniques for statistical decision making in single-case designs

The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.

Assessing functional relations in single-case designs: Quantitative proposals in the context of the evidence-based movement

In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications.

Assigning and combining probabilities in single-case designs: A second study

The present study builds on a previous proposal for assigning probabilities to the outcomes computed using different primary indicators in single-case studies. These probabilities are obtained comparing the outcome to previously tabulated reference values and reflect the likelihood of the results in case there was no intervention effect. The current study explores how well different metrics are translated into p values in the context of simulation data. Furthermore, two published multiple baseline data sets are used to illustrate how well the probabilities could reflect the intervention effectiveness as assessed by the original authors. Finally, the importance of which primary indicator is used in each data set to be integrated is explored; two ways of combining probabilities are used: a weighted average and a binomial test. The results indicate that the translation into p values works well for the two nonoverlap procedures, with the results for the regression-based procedure diverging due to some undesirable features of its performance. These p values, both when taken individually and when combined, were well-aligned with the effectiveness for the real-life data. The results suggest that assigning probabilities can be useful for translating the primary measure into the same metric, using these probabilities as additional evidence on the importance of behavioral change, complementing visual analysis and professional's judgments.

Informal communication networks and the diffusion of innovations in UK construction projects: A research design

The UK industry has been criticised for being slow to adopt construction process innovations. Research shows that the idiosyncrasies of participants, their roles in the system and the contextual differences between sections of the industry make this a highly complex problem. There is considerable evidence that informal social networks play a key role in diffusion of innovations. The aim is to identify informal communication networks of project participants and the role these play in the diffusion of construction innovations. The characteristics of this network will be analysed in order to understand how they can be used to accelerate innovation diffusion within and between projects. Social Network Analysis is used to determine informal communication routes. Control and experiment case study projects are used within two different organizations. This allows informal communication routes concerning innovations to be mapped, whilst testing if the informal routes can facilitate diffusion. Analysis will focus upon understanding the combination of informal strong and weak ties, and how these impede or facilitate the diffusion of the innovation. Initial work suggests the presence of an informal communication network. Actors within this informal network, and the organization's management are unaware of its' existence and their informal roles within it. Thus, the network remains an untapped medium regarding innovation diffusion. It is proposed that successful innovation diffusion is dependent upon understanding informal strong and weak ties, at project, organization and industry level.

The temporal evolution of nonverbal synchrony in outpatient psychotherapy: An aggregation of single-case studies

Objective: The authors quantified nonverbal synchrony—the coordination of patient's and therapist's movement—in a random sample of same-sex psychotherapy dyads. The authors contrasted nonverbal synchrony in these dyads with a control condition and assessed its association with session-level and overall psychotherapy outcome. Method: Using an automated objective video analysis algorithm (Motion Energy Analysis; MEA), the authors calculated nonverbal synchrony in (n = 104) videotaped psychotherapy sessions from 70 Caucasian patients (37 women, 33 men, mean age = 36.5 years, SD = 10.2) treated at an outpatient psychotherapy clinic. The sample was randomly drawn from an archive (N = 301) of routinely videotaped psychotherapies. Patients and their therapists assessed session impact with self-report postsession questionnaires. A battery of pre- and postsymptomatology questionnaires measured therapy effectiveness. Results: The authors found that nonverbal synchrony is higher in genuine interactions contrasted with pseudointeractions (a control condition generated by a specifically designed shuffling procedure). Furthermore, nonverbal synchrony is associated with session-level process as well as therapy outcome: It is increased in sessions rated by patients as manifesting high relationship quality and in patients experiencing high self-efficacy. Higher nonverbal synchrony characterized psychotherapies with higher symptom reduction. Conclusions: The results suggest that nonverbal synchrony embodies the patients' self-reported quality of the relationship and further variables of therapy process. This hitherto overlooked facet of therapeutic relationships might prove useful as an indicator of therapy progress and outcome. (PsycINFO Database Record (c) 2015 APA, all rights reserved)

Guidelines for deepwater port single point mooring design /

Prepared by Exxon Research and Engineering Co. under contract DOT-CG-62451-A.

Single-subject research designs and data analyses for assessing elite athletes' conditioning

Research in conditioning (all the processes of preparation for competition) has used group research designs, where multiple athletes are observed at one or more points in time. However, empirical reports of large inter-individual differences in response to conditioning regimens suggest that applied conditioning research would greatly benefit from single-subject research designs. Single-subject research designs allow us to find out the extent to which a specific conditioning regimen works for a specific athlete, as opposed to the average athlete, who is the focal point of group research designs. The aim of the following review is to outline the strategies and procedures of single-subject research as they pertain to.. the assessment of conditioning for individual athletes. The four main experimental designs in single-subject research are: the AB design, reversal (withdrawal) designs and their extensions, multiple baseline designs and alternating treatment designs. Visual and statistical analyses commonly used to analyse single-subject data, and advantages and limitations are discussed. Modelling of multivariate single-subject data using techniques such as dynamic factor analysis and structural equation modelling may identify individualised models of conditioning leading to better prediction of performance. Despite problems associated with data analyses in single-subject research (e.g. serial dependency), sports scientists should use single-subject research designs in applied conditioning research to understand how well an intervention (e.g. a training method) works and to predict performance for a particular athlete.

A kutatási és fejlesztési tevékenység lehetőségei és korlátai a kkv szektorban = Opportunities and constrains in the r&d activities of the smes: description of the research design and the analyzed cases

Ezen kutatási tanulmány módszertani összefoglalója a Kutatási és fejlesztési tevékenység lehetőségei és korlátai a KKV szektorban című kutatási műhely tanulmányainak. A kutatók feltáró, kvalitatív kutatás végeztek, azon belül pontosabban kvalitatív mélyinterjúkon alapuló esettanulmányos kutatást. A kutatók 14 kis- és középvállalkozás vezetőjével készítettek mélyinterjút annak érdekében, hogy feltárják a kis- és középvállalkozások adaptációs és növekedési lehetőségeit és korlátait, valamint az innovációs tevékenységének lehetőségeit és korlátait. Jelen tanulmány röviden bemutatja a vizsgált 14 esetet is. / === / This research paper is the methodological summary of the research working papers entitled Opportunities and constraints in the R&D activities of the SMES. The researchers carried out an explorative, qualitative research, to be more exact a case study research based on qualitative interviews. The researchers conducted interviews with CEOs of 14 SMEs in order to explore the opportunities and constraints in the adaptation and growth potential and in the innovation activities of the SMEs. This paper introduces in brief the analysed 14 case study, too.

Initial dilemmas in IST research: design science and design research, a clarification of concepts

The inter-disciplinarity of information systems, applied discipline and activity of design, and the study from different paradigms perspectives explains the diversity of problems addressed. The context is broad and includes important issues beyond technology, as the application, use, effectiveness, efficiency and their organizational and social impacts. In design science, the research interest is in contributing to the improvement of the processes of the design activity itself. The relevance of research in design science is associated with the result obtained for the improvement of living conditions in organizational, inter-organizational and Society contexts. In the research whose results are artifacts, the adoption of design research as a process of research is crucial to ensure discipline, rigor and transparency. Based on a literature review, this paper clarifies the terms of design science and design research. This is the main motivation for presenting this paper, determinant for the phase in research in technologies and information systems which are the three research projects presented. As a result the three projects are discussed in relation to the concepts of design science and design research.

Interpretative research in information systems: two qualitative research design projects

In a scientific research project is important to define the underlying philosophical orientation of the project, because this will influence the choices made in respect of scientific methods used, as well as the way they will be applied. It is crucial, therefore, that the philosophy and research design strategy are consistent with each other. These questions become even more relevant in qualitative research. Historically, the interpretive research philosophy is more associated to the scientific areas of social sciences and humanities where the subjectivity inherent to human intervention is more explicitly defined. Information systems field are, primarily, trapped in computer science field, though it also integrates issues related with management and organizations field. This shift from a purely technological guidance for the consideration of the problems of management and organizations has fostered the rise of research projects according to the interpretive philosophy and using qualitative methods. This paper explores the importance of alignment between the epistemological orientation and research design strategy, in qualitative research projects. As a result, it is presented two PhD projects, with different research design strategies, that are being developed in the technology and information systems field, in the light of the interpretive paradigm.

Positive effects of an angiotensin II type 1 receptor antagonist in Camurati-Engelmann disease: a single case observation.

Camurati-Engelmann disease is characterized by hyperostosis of the long bones and the skull, muscle atrophy, severe limb pain, and progressive joint contractures in some patients. It is caused by heterozygous mutations in the transforming growth factor β1 (TGFβ1) believed to result in improper folding of the latency-associated peptide domain of TGFβ1 and thus in increased or deregulated bioactivity. Losartan, an angiotensin II type 1 receptor antagonist, has been found to downregulate the expression of TGFβ type 1 and 2 receptors. Clinical trials with losartan have shown a benefit in Marfan syndrome, while trials are underway for Duchenne muscular dystrophy and other myopathies associated with TGFβ1 signaling. We hypothesized that due to its anti-TGFβ1 activity, losartan might be beneficial in Camurati-Engelmann disease. This report concerns a boy who presented at age 13 years with severe limb pain and difficulty in walking. Clinical and radiographic evaluation results were compatible with Camurati-Engelmann disease and the diagnosis was confirmed by mutation analysis (c.652C > T [p.Arg218Cys]). The boy underwent an experimental treatment with losartan at a dosage of 50 mg/day, orally. During the treatment period of 18 months, the intensity and frequency of limb pain decreased significantly (as shown by a pain diary), and muscle strength improved, allowing the boy to resume walking and climbing stairs. No obvious side effects were observed. We cautiously conclude that TGFβ1 inhibition with losartan deserves further evaluation in the clinical management of Camurati-Engelmann disease.