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We define the first as “internal respon-siveness,” which characterizes the ability of a measure to change over a particular prespecified time frame. One widely used method of assessing internal responsiveness is to evaluate the change in a measure within the context of a randomized clinical trial involving a treatment that has pre-
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A review of the literature suggests there are two major aspects of responsiveness. We define the first as "internal responsiveness," which characterizes the ability of a measure to change over a prespecified time frame, and the second as "external responsiveness, " which reflects the extent to which ….
- Janice A. Husted, Richard J. Cook, Vern T. Farewell, Dafna D. Gladman
- 2000
- Types of Data
- Measurement Error and Bias
- How to Control For Measurement Errors?
- Clinimetric Properties of Measurements
Measurements of clinical phenomena yield four main types of data: nominal, ordinal, interval, and continuous.6 Nominal datadoes not have meaning beyond representing unordered categories despite numbers often being used to represent the categories, such as, languages (German, French, English, Spanish), blood types (A, B, O, AB), sex (female, male), ...
Irrespective of whether we are interpreting a diagnostic test or a clinical finding, determining eligibility for a study, defining and/or quantifying an intervention or an exposure, or quantifying an outcome, we are using a quantitative measurement system in some form to describe a behavior or characteristic. In each of these situations we must sep...
Strategies to reduce measurement bias include: 1. Standardize measurement methods: • Educate subjects to follow instructions before assessment (e.g., to drink the amount of oral contrast prescribed prior to a CT scan of the abdomen)—to minimize subject variability • Mandate technique (e.g., standardize imaging protocols in an operations’ manual)—to...
There are three main clinimetric properties of measurements: reliability, validity, and responsiveness.
We identified three distinct but overlapping conceptualisations of responsiveness in the literature, corresponding to domains of literature relating to service quality; inequalities and the needs of diverse groups (in health or other services); and consumerism and patient involvement.
- Carolyn Tarrant, Emma Angell, Richard Baker, Mary Boulton, George Freeman, Patricia Wilkie, Peter Ja...
- 2014/11
- 2014
The COSMIN group defined responsiveness as “the ability of an instrument to detect change over time in the construct to be measured.” According to this definition, responsiveness is an aspect of validity. However, other authors use different definitions and subsequently, different methods.
- cb.terwee@vumc.nl
Sep 9, 2020 · Explanatory & Response Variables: Definition & Examples. by Zach Bobbitt September 9, 2020. Two of the most important types of variables to understand in statistics are explanatory variables and response variables.
Statistical inference uses probability to determine how confident we can be that our conclusions are correct. Effective interpretation of data, or inference, is based on good procedures for producing data and thoughtful examination of the data.
