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Introduction and Brief History of Structural Equation Modeling for Health and Medical Research
Published in Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle, Structural Equation Modeling for Health and Medicine, 2021
Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle
In conducting experimental research, the researcher maintains control over the environment (i.e. design and setting of the study) and is able to manipulate the boundaries on the primary independent variable. Experimental research is performed prospectively, and an intervention is tested in a regulated environment. For example, in a randomized, controlled clinical trial of a new sodium chloride tablet for patients with low sodium level, each patient is randomly assigned to receive the tablet or a placebo (a binary independent variable). The patients could be randomized into the treatment arm using stratification or minimization as well as a block design. As a result of the study design (and given a large enough sample), potential confounders such as age, gender and race should be approximately evenly distributed at least in theory between tablet and placebo group.
Preparing the Patient for the fMRI Study and Optimization of Paradigm Selection and Delivery
Published in Andrei I. Holodny, Functional Neuroimaging, 2019
Every fMRI paradigm (for clinical purposes) requires both resting and active states. The most common paradigm design for use in patients is termed “block design” and consists of a periodic (or nonperiodic) presentation of stimuli in blocks (Fig. 7). For example, in a typical block-designed finger-tapping protocol, the patient alternates between fixation on a crosshair on a screen for 20 seconds and finger tapping for 20 seconds. Many paradigms repeat this cycle for five or six trials.
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Published in Filomena Pereira-Maxwell, Medical Statistics, 2018
Simple randomization and block randomization result in parallel group comparisons (unmatched and matched). Blocking can be made more efficient still by treating each patient as a ‘treatment block’, i.e. by administering all treatments under study to each and all study participants, as in a repeated measurements randomized block design, or in a two-period or multiperiod crossover trial. These are examples of one-factor designs in which there is a single treatment factor, which is the factor of interest, and one or two blocking factors. In clinical experiments, there is often interest in the joint effect or interaction between two (or more) factors. Factorial and split-plot designs may be used to this aim, the former corresponding to a comparison between independent groups, and the latter to independent-group comparisons between levels of factor A, and within-subject comparisons between levels of factor B (i.e. it also involves repeated measurements). See FLEISS (1999), ARMITAGE, BERRY & MATHEWS (2002), MACHIN & CAMPBELL (2005) and HUITEMA (2011) for further details and illustrative examples. See also clinical trial, intervention study.
Testing mediational processes of substance use relapse among youth who participated in a mobile texting aftercare project
Published in Substance Abuse, 2022
Rachel Gonzales-Castaneda, James R. McKay, Jane Steinberg, Ken C. Winters, Chong Ho (Alex) Yu, Irene C. Valdovinos, Janna M. Casillas, Kyle C. McCarthy
Caution should be taken when interpreting the results of this exploratory study for several reasons: (1) the findings are based on a small pilot study; (2) the youth sample is limited to those who completed treatment and self-selected to participate; and (3) although participants were randomly assigned to each condition, there was a higher proportion of participants in the target condition reporting methamphetamine as the primary substance used (37%) whereas a majority (48.8%) reporting marijuana use in the control condition. Future studies may utilize a randomized block design to account for important differences that may affect outcomes, such as substance use type or substance use severity. Additionally, the single item measure for extracurricular participation did not assess duration or intensity and therefore a threshold which begins impacting primary outcomes cannot be established. In addition, this study did not look at specific extracurricular activities that are important for youth in recovery, but a generic emphasis on positive pro-social activities that are commonly referenced in the larger literature among youth. Lastly, the study included a methodological limitation with a lack of a mobile control condition which limited our ability to examine effects of exposure to alternative mobile texting interventions; however, it should be noted that this was a pilot study that sought the initial efficacy and feasibility of mobile texting for aftercare compared to standard aftercare as usual.
Psychological and endocannabinoid responses to aerobic exercise in substance use disorder patients
Published in Substance Abuse, 2021
Angelique G. Brellenthin, Kevin M. Crombie, Cecilia J. Hillard, Randall T. Brown, Kelli F. Koltyn
During a baseline study visit, participants completed questionnaires on demographics, substance use history (Timeline Follow Back),31 and severity (Severity of Dependence Scale).32 Participants also provided information on depression (Patient Health Questionnaire-9)33 and anxiety (Generalized Anxiety Disorder-7 item),34 self-efficacy to abstain (Situational Confidence Questionnaire),35 and stress (Perceived Stress Scale)36 both at baseline and 6 weeks. At the end of the baseline visit, they were randomized to either 6 weeks of treatment-as-usual (TAU; control) or TAU plus exercise (EX). Six weeks was selected as the duration from both a practical and translational perspective since 6 weeks was the average length of the five local IOP treatment programs, and all participants were concurrently attending their IOP during their study participation. The randomization sequence was generated by the study coordinator using a free online service. Randomization followed a stratified block design using sequences of permuted blocks of equal length containing the treatment assignments. The pre-defined strata were based on the participant’s treatment clinic (e.g., 1 of the 5 local IOPs).
Type-I intermittency from Markov binary block visibility graph perspective
Published in Journal of Applied Statistics, 2021
Pejman Bordbar, Sodeif Ahadpour
In this section, we demonstrate the binary block design in order to optimize the Markov binary visibility graph to analyze laminar and chaotic zones in the type-I intermittency. The block design is a topic in combinatorial mathematics which can be used in all or part of methods and also for algorithms of taxonomy in order to boost classifications of various phenomena in applied sciences [6,29]. A block design is the type of experimental design which 7]. A block design is binary if all of arrays 7]. In the other words, if each treatment occurs at most once in a block, the design is a Binary Block Design (BBD) [4]. The BBD has more applications in pure and applied Sciences [12–14].