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Given the wide range of the dependent variable for each category and that the groups overlap, correlated measurement error should not be an issue here.26.26
We predicted success on individual trials using a linear-mixed effect model [22] with a logit as a linking function because of the limited range of the dependent variable ([0, 1]).
Although there are currently no guidelines as to what constitutes an acceptable goodness-of-fit for a mapping study, a recent systematic review of published mapping studies for various disease states by Brazier et al 9 found MAEs ranging between 0.0011 and 0.19, representing a percentage error of up to 15 of the overall scale range of the dependent variable.
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Although the sizes of the coefficients are not directly comparable because of different ranges of the dependent variable (the TTO values), the relative importance of the domains within each regression model can still be compared.
Only 6% of predicted values fell outside the range (1 – 4) of the dependent variable; all of the predicted values falling outside this range exceeded the maximum value for this variable (4), with none higher than 4.19.
Statistical analyses were conducted using ANOVA for repeated measures to test for interaction effects of available charging stations and remaining range with the dependent variable range anxiety.
Thus we repeated the multiple regression with normalized peak force over the whole range of effort as the dependent variable and theta/alpha and high frequency power changes and the difference in gamma and beta band power changes as the independent variables.
This means that even if the dimensions of a particular instance fall within the range of the others, the value of the dependent variable may have very different values from those of the other instances.
The Tobit model was used on the basis of measurement of the dependent variable y (ranging between 0 and 1) which was the proportion of heifers that failed to reach first calving age.
The reasonable dependence of a variable can be verified through the coefficient of determination (R 2) which ranges between 0 and 1 signposting the predictable extent of the dependent variable.
The parameter estimates of the first order autocorrelation coefficient ranged between 0.920 and 0.983, indicating a highly autoregressive correlation among the different time points of the dependent variable.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com