### Table 9. Influential Factors in Increased Transit Use for the Proposed Systems

1997

"... In PAGE 18: ... 5. SUMMARY OF MODEL RESULTS Table9 summarizes the factors affecting the increased use of transit by disabled travelers as a result of an on-board system, kiosk system, in-home, and personal system as well as the use of... ..."

### Table 4.1. Polarity Values for Sample Influential Blogs From-To Number of links Polarity before

2007

Cited by 7

### Table 6 Usability sub-characteristics and the measures that explain them Sub-characteristic Influential combination of measures

2006

"... In PAGE 11: ...97. These combi- nations are shown in Table6 and, among other things, provide very interesting information about the existing links between the component attributes and the Quality Model, i.e.... In PAGE 11: ... Hence, we can see how these two measurable concepts have influence on the three Usability sub-characteristics (on more or less degree, of course). Please notice as well that some of the equations in Table6 do not include measures that were very influen- tial on their own. This means that a combination of less representative measures may become more representa- tive than the individual measures themselves, and than any other individual measure.... ..."

Cited by 2

### Table 6. Summary of factors identified by families as being influential on their decisions to attend the SFP10-14

2006

### Table 2. Influential fuzzy if-then rules for estimating the value of each market.

"... In PAGE 22: ... Thus the target output for each market was the same after the 14th round. As a result, the consequent real numbers for each market were almost the same in the seven fuzzy if-then rules in Table2 . While Table 2 was obtained from a single trial, almost the same results were obtained from other trials with different random market selection in the first two rounds.... ..."

### Table 1 shows CRA statistics for the term quality and influential terms linked to it. In these data

### TABLE V COMPARISON OF THE MOST INFLUENTIAL DESIGN VARIABLE FOR THE OBJECTIVE FUNCTIONS BETWEEN ANOVA AND SOM.

### Tables 1 and 2 summarize the information on consensus clusters and their influential attributes found in the results reports.

2006

### TABLE 7a. REGRESSION DIAGNOSTICS: DROPPING INFLUENTIAL OBSERVATIONS in Model 3 (H1) (OLS w/robust standard errors)

in Electoral Rules As Constraints On Corruption: The Risks Of Closed-List Proportional Representation

"... In PAGE 40: ...40 TABLE7 b. REGRESSION DIAGNOSTICS: DROPPING INFLUENTIAL OBSERVATIONS in Model 1(H2) (OLS w/robust standard errors) Dropping large STUDENT Dropping large Dfdsize Dropping large Dfclist Dropping large DFFITS Coeff p-value Coeff p-value Coeff p- value Coeff p- valu e DISTSIZE ***-0.... In PAGE 40: ...92 Obs. 54 51 53 50 TABLE7 c. REGRESSION DIAGNOSTICS: DROPPING INFLUENTIAL OBSERVATIONS in Model 2(H3) (OLS w/robust standard errors) Dropping large STUDENT Dropping large Dfclpres Dropping large DFFITS Coeff p-value Coeff p-value Coeff p- value CLPRES ***-0.... ..."

### TABLE 7b. REGRESSION DIAGNOSTICS: DROPPING INFLUENTIAL OBSERVATIONS in Model 1(H2) (OLS w/robust standard errors)

in Electoral Rules As Constraints On Corruption: The Risks Of Closed-List Proportional Representation

"... In PAGE 39: ...39 TABLE7 a. REGRESSION DIAGNOSTICS: DROPPING INFLUENTIAL OBSERVATIONS in Model 3 (H1) (OLS w/robust standard errors) Dropping large STUDENT Dropping large DFclpr Dropping large DFFITS Coeff p-value Coeff p-value Coeff p-value CLPR ***- 0.... In PAGE 40: ... TABLE7 c. REGRESSION DIAGNOSTICS: DROPPING INFLUENTIAL OBSERVATIONS in Model 2(H3) (OLS w/robust standard errors) Dropping large STUDENT Dropping large Dfclpres Dropping large DFFITS Coeff p-value Coeff p-value Coeff p- value CLPRES ***-0.... ..."