### Table 5: Predictive Validity Structural

"... In PAGE 28: ... Predictive Validity We assess predictive validity by examining whether the distinction between the five configurations is useful in predicting differences along other quot;dependent quot; variables -- reflecting the performance of the relations. Table5... ..."

### TABLE 2. Indexes of Predictive Validity

in Late-Systolic Pumping Properties of the Left Ventricle Deviation From Elastance-Resistance Behavior

2008

### Table 4: Mission Space Model Predictive Validation

"... In PAGE 5: ... The percent difference between predicted responses (using RSEs) and actual responses (using analysis code) for the random cases is used as a measure of the RSE accuracy. Table 3: Ranges for Mission Space Model Mission Parameter Units Minimum Maximum Payload lbs 30000 50000 Altitude feet 0 4000 Temperature F 90 95 Hover 1 Time min 1 5 Cruise 1 Combat Radius nm 50 540 Payload Dropped % 50 100 Cruise 3 Comabt Radius nm 50 530 Cruis 3 Altitude feet 0 8000 Cruise 3 Temperature ISA + C 0 30 Hover 2 Time min 2 5 Vertical ROC fpm 0 500 Flat Plate Drag Area sq feet 0 45 The results of this confirmation test are given in Table4 . This table shows the maximum, mean and standard deviation for the percent difference between the predicted response and the actual response (per analysis code) for the random cases.... ..."

Cited by 1

### Table 4. Logistic Regression Results Single Segment

2000

"... In PAGE 23: ... Specifically, we model purchasing in each session as a function of (1) the number of past visits, (2) the number of past purchases, (3) the number of visits since the last purchase, (4) time elapsed (in days) since the last visit, and (5) time elapsed (in days) since the last purchase. The results of the logistic regression are presented in Table4 . The fit of the model is vastly inferior to that of the Conversion Model.... ..."

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### Table 14: Different correlational approaches for evaluating predictive validity.

1999

"... In PAGE 60: ... Correlational approaches to evaluating the predictive validity of a process capability measure can be classified by the manner in which the variables are measured. Table14 shows a classification of approaches. The columns indicate the manner in which the criterion is measured.... In PAGE 61: ... This usually translates into smaller sample sizes and hence reduced statistical power. Therefore, the selection of a quadrant in Table14 is a tradeoff among cost, measurement rigor, and generalizability. Many previous studies that evaluated the relationship between process capability (or organizational maturity) and the performance of projects tended to be in quadrant Q1.... ..."

### Table 4: Correlation coefficients and errors of prediction for the validation set.

"... In PAGE 17: ...When the water bodies with odd sample numbers (N =29) were used for model 421 calibration and those with even sample numbers (N = 28) were used as validation sets, the 422 correlation coefficients (R2) of plots of the observed and predicted variable values together 423 with the root mean square errors of prediction (RMSEP) are presented in Table4 . Given the 424 facts that (i) the water bodies are from widely different origins, (ii) the studies were 425 undertaken under different conditions and (iii) the limit of acceptable R2 at 95% coefficient 426 level is 0.... ..."

### Table 2: Prediction Error on Validation Set

1997

"... In PAGE 14: ... Using the coe cients estimated on the 330-patient training dataset, we form predictions for the remaining 810 patients in the database for whom the records were complete. We can quantify the error with the validation U2 2 , the ratio of the squared prediction error to the variance of the true values of the Mississippi Scale in the 810-observation validation sample, and with U1 = P810 i=1 jyi ? ^ yij P810 i=1 jyi ? yj : The values of the two prediction error measures for the four methods are given in Table2 . The t is plainly not very good for any of the four methods.... ..."

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