Related Research Articles
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures used to analyze the differences between groups. It uses F-test by comparing variance between groups and taking noise, or assumed normal distribution of group, into consideration by dividing by variance between elements in a group. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means.
The design of experiments, also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation.
An experiment is a procedure carried out to support or refute a hypothesis, or determine the efficacy or likelihood of something previously untried. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in goal and scale but always rely on repeatable procedure and logical analysis of the results. There also exist natural experimental studies.
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size value. Examples of effect sizes include the correlation between two variables, the regression coefficient in a regression, the mean difference, or the risk of a particular event happening. Effect sizes are a complement tool for statistical hypothesis testing, and play an important role in power analyses to assess the sample size required for new experiments. Effect size are fundamental in meta-analyses which aim to provide the combined effect size based on data from multiple studies. The cluster of data-analysis methods concerning effect sizes is referred to as estimation statistics.
Field experiments are experiments carried out outside of laboratory settings.
Applied behavior analysis (ABA), also referred to as behavioral engineering, is a psychological discipline that applies the principles of learning based upon respondent and operant conditioning to change socially significant behavior. ABA is the applied form of behavior analysis. The impact ABA has on meaningful behaviors is a defining feature, and what differentiates it from experimental analysis of behavior, which focuses on basic experimental research.
In the statistical theory of the design of experiments, blocking is the arranging of experimental units that are similar to one another in groups (blocks) based on one or more variables. These variables are chosen carefully to minimize the impact of their variability on the observed outcomes. There are different ways that blocking can be implemented, resulting in different confounding effects. However, the different methods share the same purpose: to control variability introduced by specific factors that could influence the outcome of an experiment. The roots of blocking originated from the statistician, Ronald Fisher, following his development of ANOVA.
Behaviour therapy or behavioural psychotherapy is a broad term referring to clinical psychotherapy that uses techniques derived from behaviourism and/or cognitive psychology. It looks at specific, learned behaviours and how the environment, or other people's mental states, influences those behaviours, and consists of techniques based on behaviorism's theory of learning: respondent or operant conditioning. Behaviourists who practice these techniques are either behaviour analysts or cognitive-behavioural therapists. They tend to look for treatment outcomes that are objectively measurable. Behaviour therapy does not involve one specific method, but it has a wide range of techniques that can be used to treat a person's psychological problems.
External validity is the validity of applying the conclusions of a scientific study outside the context of that study. In other words, it is the extent to which the results of a study can generalize or transport to other situations, people, stimuli, and times. Generalizability refers to the applicability of a predefined sample to a broader population while transportability refers to the applicability of one sample to another target population. In contrast, internal validity is the validity of conclusions drawn within the context of a particular study.
In causal inference, a confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations. The existence of confounders is an important quantitative explanation why correlation does not imply causation. Some notations are explicitly designed to identify the existence, possible existence, or non-existence of confounders in causal relationships between elements of a system.
Single-subject research is a group of research methods that are used extensively in the experimental analysis of behavior and applied behavior analysis with both human and non-human participants. This research strategy focuses on one participant and tracks their progress in the research topic over a period of time. Single-subject research allows researchers to track changes in an individual over a large stretch of time instead of observing different people at different stages. This type of research can provide critical data in several fields, specifically psychology. It is most commonly used in experimental and applied analysis of behaviors. This research has been heavily debated over the years. Some believe that this research method is not effective at all while others praise the data that can be collected from it. Principal methods in this type of research are: A-B-A-B designs, Multi-element designs, Multiple Baseline designs, Repeated acquisition designs, Brief experimental designs and Combined designs.
A quasi-experiment is an empirical interventional study used to estimate the causal impact of an intervention on target population without random assignment. Quasi-experimental research shares similarities with the traditional experimental design or randomized controlled trial, but it specifically lacks the element of random assignment to treatment or control. Instead, quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment.
Impact evaluation assesses the changes that can be attributed to a particular intervention, such as a project, program or policy, both the intended ones, as well as ideally the unintended ones. In contrast to outcome monitoring, which examines whether targets have been achieved, impact evaluation is structured to answer the question: how would outcomes such as participants' well-being have changed if the intervention had not been undertaken? This involves counterfactual analysis, that is, "a comparison between what actually happened and what would have happened in the absence of the intervention." Impact evaluations seek to answer cause-and-effect questions. In other words, they look for the changes in outcome that are directly attributable to a program.
Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.
Clinical trials are medical research studies conducted on human subjects. The human subjects are assigned to one or more interventions, and the investigators evaluate the effects of those interventions. The progress and results of clinical trials are analyzed statistically.
A glossary of terms used in experimental research.
A glossary of terms used in clinical research.
An N of 1 trial (N=1) is a multiple crossover clinical trial, conducted in a single patient. A trial in which random allocation is used to determine the order in which an experimental and a control intervention are given to a single patient is an N of 1 randomized controlled trial. Some N of 1 trials involve randomized assignment and blinding, but the order of experimental and control interventions can also be fixed by the researcher.
A multiple baseline design is used in medical, psychological, and biological research. The multiple baseline design was first reported in 1960 as used in basic operant research. It was applied in the late 1960s to human experiments in response to practical and ethical issues that arose in withdrawing apparently successful treatments from human subjects. In it two or more behaviors, people or settings are plotted in a staggered graph where a change is made to one, but not the other two, and then to the second, but not the third behavior, person or setting. Differential changes that occur to each behavior, person or in each setting help to strengthen what is essentially an AB design with its problematic competing hypotheses.
A consecutive controlled case series (CCCS) is a clinical study that involves aggregating multiple cases consecutively encountered wherein an experimentally controlled single-case experimental design was employed with each case. The CCCS design differs from the consecutive case series, because the latter reports on multiple cases where experimental control was not demonstrated, usually because a pre-post non experimental design was used. In contrast, a CCCS includes only cases where the intervention was evaluated using single-case experimental designs, such as a reversal design, where experimental control is demonstrated through the replication of treatment effects for each individual participant. Thus, the CCCS design has better internal validity than a consecutive case series. The CCCS design also address some concerns about the external validity or generality of findings of small-n single-case experimental design studies because it explicitly includes all cases encountered, regardless of outcome. By including all cases, any bias favoring a particular outcome in controlled for, resulting in stronger external validity relative to studies describing fewer cases that were not consecutively encountered. Moreover, when a large number of individuals are included in the series, this provides opportunities to identify variables that may predict treatment outcomes. Consecutive controlled case-series studies examining behavior analytic interventions of late have examined functional communication training. schedule thinning during functional communication training, and functional analysis and treatment using caregivers.
References
- 1 2 3 4 5 Cooper, J. O., Heron, T. E., & Heward, W. L. (2007). Applied behavior analysis (2nd ed.). Columbus, OH: Merrill Prentice Hall.
- ↑ Cooper, J.O.; Heron, T.E.; Heward, W.L. (2007). Applied Behavior Analysis (2nd ed.). Prentice Hall. ISBN 978-0-13-142113-4.
- ↑ Kazdin p. 191
- ↑ Kratochwill, T. R., Hitchcock, J., Horner, R. H., Levin, J. R., Odom, S. L., Rindskopf, D. M & Shadish, W. R. (2010). Single-case designs technical documentation. Retrieved from What Works Clearinghouse website: https://ies.ed.gov/ncee/wwc/Docs/ReferenceResources/wwc_scd.pdf Archived 2022-09-01 at the Wayback Machine .
- ↑ Tate, R. L., Perdices, M., Rosenkoetter, U., McDonald, S., Togher, L., Shadish, W., . . . Vohra, S. (2016). The Single-Case Reporting Guideline In BEhavioural Interventions (SCRIBE) 2016: Explanation and elaboration. Archives of Scientific Psychology, 4(1), 10-31. doi : 10.1037/arc0000027
- ↑ Backman, C.L. & Harris, S.R. (1999). Case Studies, Single-Subject Research, and N of 1 Randomized Trials. Comparisons and Contrasts. American Journal of Physical Medicine & Rehabilitation, 78(2), 170–6.
- ↑ Bobrovitz, C.D. & Ottenbacher, K.J. (1998). Comparison of Visual Inspection and Statistical Analysis of Single-Subject Data in Rehabilitation Research. Journal of Engineering and Applied Science, 77(2), 94–102.
- ↑ Nishith, P.; Hearst, D.E.; Mueser, K.T. & Foa, E. (1995). PTSD and Major Depression: Methodological and Treatment Considerations in a Single-Case Design. Behavior Therapy, 26(2), 297–9
- ↑ Horner, Robert, Carr, Edward, Halle, Jim, Mcgee, Gail, SL, Odom & Wolery, Mark. (2005). The Use of Single-Subject Research to Identify Evidence-Based Practice in Special Education. Exceptional Children. 71. 165-179. 10.1177/001440290507100203.
- ↑ Kazdin, p. 284
- ↑ Kazdin, p. 291