Inter-rater Reliability
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Inter-rater Reliability
In statistics, inter-rater reliability (also called by various similar names, such as inter-rater agreement, inter-rater concordance, inter-observer reliability, inter-coder reliability, and so on) is the degree of agreement among independent observers who rate, code, or assess the same phenomenon. Assessment tools that rely on ratings must exhibit good inter-rater reliability, otherwise they are not valid tests. There are a number of statistics that can be used to determine inter-rater reliability. Different statistics are appropriate for different types of measurement. Some options are joint-probability of agreement, such as Cohen's kappa, Scott's pi and Fleiss' kappa; or inter-rater correlation, concordance correlation coefficient, intra-class correlation, and Krippendorff's alpha. Concept There are several operational definitions of "inter-rater reliability," reflecting different viewpoints about what is a reliable agreement between raters. There are three operational defin ...
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Test Validity
Test validity is the extent to which a test (such as a chemical test, chemical, physical test, physical, or test (assessment), scholastic test) accuracy and precision, accurately measures what it is supposed to measure. In the fields of psychological testing and test (assessment), educational testing, "validity refers to the degree to which evidence and theory support the interpretations of test scores entailed by proposed uses of tests".American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999) ''Standards for educational and psychological testing''. Washington, DC: American Educational Research Association. Although classical models divided the concept into various "validities" (such as content validity, criterion validity, and construct validity),Guion, R. M. (1980). On trinitarian doctrines of validity. ''Professional Psychology, 11'', 385-398. the currently dominant view is that validity is a single unitar ...
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Spearman's Rank Correlation Coefficient
In statistics, Spearman's rank correlation coefficient or Spearman's ''ρ'', named after Charles Spearman and often denoted by the Greek letter \rho (rho) or as r_s, is a nonparametric measure of rank correlation ( statistical dependence between the rankings of two variables). It assesses how well the relationship between two variables can be described using a monotonic function. The Spearman correlation between two variables is equal to the Pearson correlation between the rank values of those two variables; while Pearson's correlation assesses linear relationships, Spearman's correlation assesses monotonic relationships (whether linear or not). If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other. Intuitively, the Spearman correlation between two variables will be high when observations have a similar (or identical for a correlation of 1) rank (i.e. relative position lab ...
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Rating (pharmaceutical Industry)
Within the field of clinical trials, rating is the process by which a human evaluator subjectively judges the response of a patient to a medical treatment. The rating can include more than one treatment response. The accessor is normally an independent observer other than the patient, but the accessor can also be the patient (a patient-reported outcome). Furthermore, some clinical outcomes can only be assessed by the patient (a "private phenomena"). Because the evaluation is subjective, this can result in both inter-rater or intra-rater reliability. When conducting clinical trials, ensuring rating consistency is important, but can prove to be quite difficult to obtain. Studies dealing with such indications as pain, mental disease A mental disorder, also referred to as a mental illness or psychiatric disorder, is a behavioral or mental pattern that causes significant distress or impairment of personal functioning. Such features may be persistent, relapsing and remitti ... ...
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Cronbach's Alpha
Cronbach's alpha (Cronbach's \alpha), also known as tau-equivalent reliability (\rho_T) or coefficient alpha (coefficient \alpha), is a reliability coefficient that provides a method of measuring internal consistency of tests and measures. Numerous studies warn against using it unconditionally, and note that reliability coefficients based on structural equation modeling (SEM) are in many cases a suitable alternative.Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach's alpha. Psychometrika, 74(1), 107–120. Green, S. B., & Yang, Y. (2009). Commentary on coefficient alpha: A cautionary tale. Psychometrika, 74(1), 121–135. Revelle, W., & Zinbarg, R. E. (2009). Coefficients alpha, beta, omega, and the glb: Comments on Sijtsma. Psychometrika, 74(1), 145–154. Cho, E., & Kim, S. (2015). Cronbach's coefficient alpha: Well known but poorly understood. Organizational Research Methods, 18(2), 207–230. Raykov, T., & Marcoulides, G. A. (2017). Thanks ...
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Experimenter's Bias
Observer bias is one of the types of detection bias and is defined as any kind of systematic divergence from accurate facts during observation and the recording of data and information in studies. The definition can be further expanded upon to include the systematic difference between what is observed due to variation in observers, and what the true value is. Observer bias is the tendency of observers to not see what is there, but instead to see what they expect or want to see. This is a common occurrence in the everyday lives of many and is a significant problem that is sometimes encountered in scientific research and studies. Observation is critical to scientific research and activity, and as such, observer bias may be as well. When such biases exist, scientific studies can result in an over- or underestimation of what is true and accurate, which compromises the validity of the findings and results of the study, even if all other designs and procedures in the study were appropriate ...
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Computational Linguistics
Computational linguistics is an Interdisciplinarity, interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others. Sub-fields and related areas Traditionally, computational linguistics emerged as an area of artificial intelligence performed by computer scientists who had specialized in the application of computers to the processing of a natural language. With the formation of the Association for Computational Linguistics (ACL) and the establishment of independent conference series, the field consolidated during the 1970s and 1980s. The Association for Computational Linguistics defines computational linguistics as: The term "comp ...
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Observational Studies
In fields such as epidemiology, social sciences, psychology and statistics, an observational study draws inferences from a sample (statistics), sample to a statistical population, population where the dependent and independent variables, independent variable is not under the Scientific control, control of the researcher because of ethical concerns or logistical constraints. One common observational study is about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator. This is in contrast with experiments, such as randomized controlled trials, where each subject is Random assignment, randomly assigned to a treated group or a control group. Observational studies, for lacking an assignment mechanism, naturally present difficulties for inferential analysis. Motivation The independent variable may be beyond the control of the investigator for a variety of reasons: * A ran ...
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Psychometrics
Psychometrics is a field of study within psychology concerned with the theory and technique of measurement. Psychometrics generally refers to specialized fields within psychology and education devoted to testing, measurement, assessment, and related activities. Psychometrics is concerned with the objective measurement of latent constructs that cannot be directly observed. Examples of latent constructs include intelligence, introversion, mental disorders, and educational achievement. The levels of individuals on nonobservable latent variables are inferred through mathematical modeling based on what is observed from individuals' responses to items on tests and scales. Practitioners are described as psychometricians, although not all who engage in psychometric research go by this title. Psychometricians usually possess specific qualifications such as degrees or certifications, and most are psychologists with advanced graduate training in psychometrics and measurement theory. I ...
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Survey Research
In research of human subjects, a survey is a list of questions aimed for extracting specific data from a particular group of people. Surveys may be conducted by phone, mail, via the internet, and also at street corners or in malls. Surveys are used to gather or gain knowledge in fields such as social research and demography. Survey research is often used to assess thoughts, opinions and feelings. Surveys can be specific and limited, or they can have more global, widespread goals. Psychologists and sociologists often use surveys to analyze behavior, while it is also used to meet the more pragmatic needs of the media, such as, in evaluating political candidates, public health officials, professional organizations, and advertising and marketing directors. Survey research has also been employed in various medical and surgical fields to gather information about healthcare personnel’s practice patterns and professional attitudes toward various clinical problems and diseases. Healthcar ...
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Bland–Altman Plot
A Bland–Altman plot (difference plot) in analytical chemistry or biomedicine is a method of data plotting used in analyzing the agreement between two different assays. It is identical to a Tukey mean-difference plot, the name by which it is known in other fields, but was popularised in medical statistics by J. Martin Bland and Douglas G. Altman. Agreement versus correlation Bland and Altman drive the point that any two methods that are designed to measure the same parameter (or property) should have good correlation when a set of samples are chosen such that the property to be determined varies considerably. A high correlation for any two methods designed to measure the same property could thus in itself just be a sign that one has chosen a widespread sample. A high correlation does not necessarily imply that there is good agreement between the two methods. Construction Consider a sample consisting of n observations (for example, objects of unknown volume). Both assay ...
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Standard Deviation
In statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. Standard deviation may be abbreviated SD, and is most commonly represented in mathematical texts and equations by the lower case Greek letter σ (sigma), for the population standard deviation, or the Latin letter '' s'', for the sample standard deviation. The standard deviation of a random variable, sample, statistical population, data set, or probability distribution is the square root of its variance. It is algebraically simpler, though in practice less robust, than the average absolute deviation. A useful property of the standard deviation is that, unlike the variance, it is expressed in the same unit as the data. The standard deviation of a popu ...
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