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From page 295... ...
APPENDIX G 295 Let y1 , , y n be the observed values and y1 , … , y n be the predicted val ues; let the mean of the observed values be yy¯ = 1 n∑ y i ; the mean of the predicted values be y = 1 n∑ y 1 ; the residual sum of square be 2 and the total sum of squares be SS = ( y − y )
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From page 296... ...
Parameter estimates from the TEE equations developed on the main data set were used to calculate the predicted values of TEE on the external data, and those predicted values were compared to the observed (Mean) TEE values in the external validation data using the same measures described above, such as the R-squared and Pearson correlation of observed vs predicted values, as a measure of model fit and performance.
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