TY - JOUR
AU - Batterham, A M
AU - Hopkins, W G
PY - 2005
TI - A decision tree for controlled trials
SP - 33-39
JF - Sportscience
VL - 9
N1 - A decision tree for controlled trials
KW - confidence limits, confounding, covariate, inference, modeling
N2 - Data analysis that fails to account for independent groups defined by a subject characteristic (e.g., sex) or by a design characteristic (e.g., treatment order) can result in bias, confounding, and loss of precision in the outcome. Combining the outcomes from separate analyses of the groups is a robust approach to the problem that is easily achieved with the spreadsheet presented here. Differences in the outcome between groups represent the effect of the characteristic on the outcome, while the mean of the outcomes represents the outcome adjusted appropriately for the characteristic. The spreadsheet calculates confidence limits for the differences and for the mean from the confidence limits for the outcome in each group. It also presents magnitude-based inferences for the differences and mean. There are separate cells in the spreadsheet for outcomes represented by means or other normally distributed statistics, relative rates (risk, odds and hazard ratios) or other log-normally distributed statistics, and correlation coefficients.
AD - Sport and Recreation, AUT University, Auckland 0627, New Zealand. Email: will=AT=clear.net.nz
UR - http://sportsci.org/2006/wghcom.htm
ID - 5
ER -
TY - JOUR
AU - Hopkins, W G
PY - 2006
TI - Spreadsheets for analysis of controlled trials, with adjustment for a subject characteristic
SP - 46-50
JF - Sportscience
VL - 10
N1 - Spreadsheets for analysis of controlled trials, with adjustment for a subject characteristic
KW - crossover, design, inference, repeated measures, intervention, randomized, transformation, t statistic
N2 - Spreadsheets previously available at this site for analysis of controlled trials have been updated to allow inclusion of one covariate representing a subject characteristic. The spreadsheets provide estimates of the effect of an intervention adjusted to any chosen value of the covariate, thereby reducing the possibility for confounding of the effect when a characteristic such as age, fitness or sex is unequal in the experimental and control groups. The pre-test value of the dependent variable can also be included as a covariate to avoid confounding by the phenomenon of regression to the mean. Graphs of change scores plotted against the covariate show visually how the treatment effect is adjusted to the chosen value of the covariate. The spreadsheets also provide an estimate of the effect of the covariate itself, representing individual responses attributable to the covariate. Other new features of the spreadsheets include plots of raw and back-transformed means with easily modified standard-deviation bars, and qualitative inferential outcomes based on interpretation of the span of the confidence interval relative to magnitude thresholds for trivial, small, moderate, large, and very large.
AD - Sport and Recreation, AUT University, Auckland 0627, New Zealand. Email: will=AT=clear.net.nz
UR - http://sportsci.org/2006/wghcontrial.htm
ID - 1
ER -
TY - JOUR
AU - Hopkins, W G
PY - 2006
TI - A spreadsheet for combining outcomes from several subject groups
SP - 51-53
JF - Sportscience
VL - 10
N1 - A spreadsheet for combining outcomes from several subject groups
KW - confidence limits, confounding, covariate, inference, modeling
N2 - Data analysis that fails to account for independent groups defined by a subject characteristic (e.g., sex) or by a design characteristic (e.g., treatment order) can result in bias, confounding, and loss of precision in the outcome. Combining the outcomes from separate analyses of the groups is a robust approach to the problem that is easily achieved with the spreadsheet presented here. Differences in the outcome between groups represent the effect of the characteristic on the outcome, while the mean of the outcomes represents the outcome adjusted appropriately for the characteristic. The spreadsheet calculates confidence limits for the differences and for the mean from the confidence limits for the outcome in each group. It also presents magnitude-based inferences for the differences and mean. There are separate cells in the spreadsheet for outcomes represented by means or other normally distributed statistics, relative rates (risk, odds and hazard ratios) or other log-normally distributed statistics, and correlation coefficients.
AD - Sport and Recreation, AUT University, Auckland 0627, New Zealand. Email: will=AT=clear.net.nz
UR - http://sportsci.org/2006/wghcom.htm
ID - 4
ER -
TY - JOUR
AU - Hopkins, W G
PY - 2016
TI - SAS (and R) for mixed models
SP - iii
JF - Sportscience
VL - 20
N1 - SAS (and R) for mixed models
ID - 3
ER -
TY - JOUR
AU - Satterthwaite, F W
PY - 1946
TI - An approximate distribution of estimates of variance components
SP - 110-114
JF - Biometrics Bulletin
VL - 2
N1 - An approximate distribution of estimates of variance components
KW - stats, degrees of freedom, confidence limits
ID - 2
ER -