Agreement & responsiveness
Allows to calculate various indices for responsiveness, which is the ability to detect any change.
- 1st and 2nd measurement: the variables for a 1st and 2nd measurement.
- Filter: an optional filter to include only a selected subgroup of subjects (rows).
- Paired data: select this option when the variables for 1st and 2nd measurements contain paired data (measurements are repeated on the same subjects). If the 2 measurements are independent, unselect this option.
- Calculate differences as: option to calculate differences as 1st minus 2nd measurement (default is 2nd minus 1st).
- Advanced: the confidence intervals for the different indices of responsiveness are estimated using the bias-corrected and accelerated (BCa) bootstrap (Efron, 1987; Efron & Tibshirani, 1993). Click bootstrapping options such as number of replications and random-number seed. for
- The sample size, mean, variance and standard deviation of the 1st and 2nd measurement.
- The average difference between the two measurements with the pooled standard deviation and (in case of paired observations) the standard deviation of the paired differences.
Indices of responsiveness
- Effect size (ES) using baseline SD: this is the average difference divided by the standard deviation of the 1st measurement (this is Glass' Δ).
- Effect size (ES) using pooled SD: this is the average difference divided by the pooled standard deviation of both measurements (this is Cohen's d).
- Standardized response mean (SRM): this is the average difference divided by the standard deviation of the differences between the paired measurements.
- Efron B (1987) Better Bootstrap Confidence Intervals. Journal of the American Statistical Association 82:171-185.
- Efron B, Tibshirani RJ (1993) An introduction to the Bootstrap. Chapman & Hall/CRC.
- Husted JA, Cook RJ, Farewell VT, Gladman DD (2000) Methods for assessing responsiveness: a critical review and recommendations. Journal of Clinical Epidemiology 53:459-168.
- Norman GR, Wyrwich KW, Patrick DL (2007) The mathematical relationship among different forms of responsiveness coefficients. Quality of Life Research 16:815-822.
An Introduction to the Bootstrap
Bradley Efron, R.J. Tibshirani
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Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.