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21st Century Operations Using 21st Century Technologies

Effectiveness of Disseminating Traveler Information on Travel Time Reliability: Implement Plan and Survey Results Report

APPENDIX T. STATISTICAL MODEL RESULTS

For each of the detailed statistical model tables contained in this appendix, results are shown from a logistic regression fit with a positive response (usually the aggregate of several positive response categories) or an ordered set of responses (higher to lower) as a function of the dissemination method (called Treatment_Mode) and lexicon (called Treatment_Assembly), as well as covariates for a number of demographic and traveler characteristics.

In the tabular results, the first column provides the parameter in the model, followed by the particular level of the parameter, the degrees of freedom (DF), the estimate, its standard error, and a P-Value. If the P-Value is less than or equal to 0.05, it is bolded, meaning that factor level is considered to be significant compared to its reference condition. The reference conditions are not shown in the tables – for each variable they are:

  • Location – Triangle
  • Treatment_Assembly – Assembly B
  • Treatment_Mode – Web access
  • Gender – Male
  • Education – Less than college
  • Income – Under $50,000
  • Age – Under 25
  • Employment – Not full time

The average distance traveled parameter is continuous, while the peak hour and weekday parameters are percentages, and the Phase2_Count is a count. For these variables, the estimate represents a slope – the magnitude of change in the response for a one unit change in the variable.

The odds ratios reported in Chapter 9 can be derived from these tables. For instance, the results for the likelihood of participants checking TTR information for familiar trips is modeled in Table 46.

The odds ratio estimate for the 511 access respondents can be found as:

Exp(Intercept + Treatment_Mode 511 access) = Exp (-0.15 + -0.76) = 0.40

The odds ratio estimate for the Web app access respondents can be found as:

Exp(Intercept + Treatment_Mode App access) = Exp (-0.15 + -0.22) = 0.68

The odds ratio for the comparison of 511 access respondents to Web app respondents is simply the ratio of the odds ratios = 0.40/0.68 = 0.58. This value of 0.58 is what is reported in Section 9.2.3, Figure 25, for the survey question.

Frequency of Checking TTR Information during Study – Familiar Trips

The logistic regression model was fit with the probability a respondent selected a category of checking resources at least once per week compared to reporting never checking them.

Table 46. Model results – information usage for familiar trips.
Parameter Level DF Estimate Standard Error P-Value
Intercept Empty cell 1 -0.15 0.76 0.84
Location Columbus 1 0.75 0.28 0.01
Location Houston 1 0.39 0.27 0.15
Treatment_Assembly Assembly A 1 -0.13 0.18 0.49
Treatment_Mode 511 access 1 -0.76 0.23 0.00
Treatment_Mode App access 1 -0.22 0.24 0.36
Gender Female 1 -0.10 0.19 0.61
Education Bachelor degree 1 -0.48 0.26 0.06
Education Graduate/Professional degree 1 -0.51 0.28 0.07
Income $100,000 or more 1 0.01 0.32 0.97
Income $50,000-$99,999 1 0.09 0.32 0.78
Age 25-44 1 0.06 0.37 0.86
Age 45-64 1 0.75 0.40 0.06
Age 65 or older 1 -0.15 0.68 0.82
Employment Full-time employed 1 0.64 0.28 0.02
Average_Distance Empty cell 1 0.00 0.01 0.49
Peak_Hour Empty cell 1 0.01 0.00 0.11
Weekday Empty cell 1 0.00 0.01 0.69
Phase2_Count Empty cell 1 0.02 0.01 0.09

Frequency of Checking TTR Information during Study – Unfamiliar Trips

The logistic regression model was fit with the probability a respondent selected a category of checking resources at least once per week compared to reporting never checking them.

Table 47. Model results – information usage for unfamiliar trips.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 3.64 0.76 <0.005
Location Columbus 1 -0.15 0.24 0.53
Location Houston 1 0.00 0.24 0.99
Treatment_Assembly Assembly A 1 0.20 0.15 0.19
Treatment_Mode 511 access 1 -0.55 0.19 <0.005
Treatment_Mode App access 1 -0.15 0.19 0.44
Gender Female 1 -0.05 0.16 0.73
Education Bachelor degree 1 -0.11 0.20 0.59
Education Graduate/Professional degree 1 -0.01 0.22 0.97
Income $100,000 or more 1 0.09 0.27 0.74
Income $50,000-$99,999 1 0.34 0.27 0.22
Age 25-44 1 -0.65 0.35 0.06
Age 45-64 1 -0.66 0.36 0.07
Age 65 or older 1 -0.78 0.65 0.23
Employment Full-time employed 1 0.17 0.26 0.50
Average_Distance Empty cell 1 -0.01 0.00 0.14
Peak_Hour Empty cell 1 -0.01 0.00 0.01
Weekday Empty cell 1 -0.03 0.01 0.00
Phase2_Count Empty cell 1 0.00 0.01 0.94

Frequency of Changing the Plan due to TTR Information for Familiar Trips

The logistic regression model was fit with the probability a respondent selected at least one of the eight possible trip change options as a result of TTR information compared to reporting never making a trip change or only doing so with other than because of TTR information.

Table 48. Model results – behavior change for familiar trips.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1.96 0.85 0.02
Location Columbus 1 -0.05 0.29 0.86
Location Houston 1 0.73 0.30 0.02
Treatment_Assembly Assembly A 1 0.43 0.18 0.02
Treatment_Mode 511 access 1 -0.49 0.23 0.03
Treatment_Mode App access 1 -0.02 0.22 0.91
Gender Female 1 0.00 0.18 0.98
Education Bachelor degree 1 -0.62 0.24 0.01
Education Graduate/Professional degree 1 -0.98 0.27 0.00
Income $100,000 or more 1 0.06 0.32 0.86
Income $50,000-$99,999 1 0.31 0.33 0.34
Age 25-44 1 -0.01 0.43 0.99
Age 45-64 1 0.14 0.44 0.76
Age 65 or older 1 -0.22 0.81 0.78
Employment Full-time employed 1 0.22 0.33 0.50
Average_Distance Empty cell 1 0.00 0.00 0.66
Peak_Hour Empty cell 1 -0.01 0.00 0.10
Weekday Empty cell 1 -0.01 0.01 0.08
Phase2_Count Empty cell 1 -0.03 0.01 0.01

Frequency of Changing the Plan due to TTR Information for Unfamiliar Trips

The logistic regression model was fit with the probability a respondent selected at least one of the eight possible trip change options as a result of TTR information compared to reporting never making a trip change or only doing so with other than because of TTR information.

Table 49. Model results – behavior change for unfamiliar trips.
Parameter Level DF Estimate Standard Error P-Value
Intercept Empty cell 1 2.17 0.95 0.02
Location Columbus 1 -0.20 0.35 0.57
Location Houston 1 0.62 0.36 0.09
Treatment_Assembly Assembly A 1 -0.05 0.23 0.83
Treatment_Mode 511 access 1 -0.14 0.29 0.63
Treatment_Mode App access 1 0.13 0.27 0.62
Gender Female 1 0.01 0.23 0.95
Education Bachelor degree 1 -0.65 0.30 0.03
Education Graduate/Professional degree 1 -0.77 0.33 0.02
Income $100,000 or more 1 -0.15 0.39 0.70
Income $50,000-$99,999 1 0.10 0.40 0.80
Age 25-44 1 -0.08 0.47 0.86
Age 45-64 1 0.01 0.49 0.99
Age 65 or older 1 -0.47 0.90 0.60
Employment Full-time employed 1 -0.03 0.38 0.94
Average_Distance Empty cell 1 0.01 0.01 0.13
Peak_Hour Empty cell 1 -0.01 0.00 0.08
Weekday Empty cell 1 -0.01 0.01 0.29
Phase2_Count Empty cell 1 -0.05 0.02 0.00

TTR Ratings Statement 1: The Transportation Study Resource was Easy to Understand

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' agreement with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 50. Model results – travel time reliability ease of understanding.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 2.46 0.88 0.01
Intercept 2 1 2.86 0.89 0.00
Location Columbus 1 0.52 0.30 0.08
Location Houston 1 -0.06 0.30 0.83
Treatment_Assembly Assembly A 1 -0.25 0.18 0.18
Treatment_Mode 511 access 1 -0.58 0.23 0.01
Treatment_Mode App access 1 -0.17 0.23 0.45
Gender Female 1 -0.05 0.19 0.77
Education Bachelor degree 1 -0.24 0.25 0.33
Education Graduate/Professional degree 1 -0.28 0.28 0.31
Income $100,000 or more 1 0.27 0.31 0.39
Income $50,000-$99,999 1 0.76 0.32 0.02
Age 25-44 1 -0.30 0.44 0.49
Age 45-64 1 0.09 0.45 0.84
Age 65 or older 1 -0.33 0.78 0.68
Employment Full-time employed 1 0.37 0.32 0.24
Average_Distance Empty cell 1 -0.01 0.00 0.06
Peak_Hour Empty cell 1 0.00 0.00 0.86
Weekday Empty cell 1 -0.01 0.01 0.17
Phase2_Count Empty cell 1 -0.02 0.01 0.14

TTR Ratings Statement 2: Information from the Transportation Study Resource was Reliable

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' agreement with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 51. Model results – travel time reliability rating: reliability.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 1.55 0.76 0.04
Intercept 2 1 2.62 0.76 0.00
Location Columbus 1 0.05 0.27 0.86
Location Houston 1 -0.51 0.28 0.06
Treatment_Assembly Assembly A 1 0.19 0.17 0.26
Treatment_Mode 511 access 1 -0.05 0.21 0.80
Treatment_Mode App access 1 0.00 0.20 0.98
Gender Female 1 -0.15 0.17 0.39
Education Bachelor degree 1 0.00 0.22 0.99
Education Graduate/Professional degree 1 -0.49 0.24 0.04
Income $100,000 or more 1 -0.40 0.30 0.19
Income $50,000-$99,999 1 -0.18 0.31 0.56
Age 25-44 1 -0.37 0.41 0.38
Age 45-64 1 -0.22 0.42 0.61
Age 65 or older 1 0.29 0.81 0.72
Employment Full-time employed 1 0.33 0.29 0.26
Average_Distance Empty cell 1 0.00 0.00 0.38
Peak_Hour Empty cell 1 0.00 0.00 0.23
Weekday Empty cell 1 0.00 0.01 0.72
Phase2_Count Empty cell 1 -0.03 0.01 0.04

TTR Ratings Statement 3: The information from the Transportation Study Resource did NOT reduce the amount of travel time I plan for my trips

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' disagreement (rather than agreement) with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 52. Model results – travel time reliability rating: did NOT reduce planned travel time.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 0.06 0.77 0.94
Intercept 2 1 1.27 0.77 0.10
Location Columbus 1 0.08 0.32 0.79
Location Houston 1 0.07 0.33 0.83
Treatment_Assembly Assembly A 1 0.09 0.19 0.65
Treatment_Mode 511 access 1 -0.19 0.25 0.43
Treatment_Mode App access 1 0.28 0.22 0.21
Gender Female 1 -0.17 0.20 0.39
Education Bachelor degree 1 -0.45 0.24 0.06
Education Graduate/ Professional degree 1 -0.68 0.28 0.01
Income $100,000 or more 1 -0.06 0.31 0.84
Income $50,000-$99,999 1 -0.02 0.31 0.94
Age 25-44 1 -0.16 0.39 0.68
Age 45-64 1 -0.63 0.41 0.13
Age 65 or older 1 -0.59 0.86 0.49
Employment Full-time employed 1 -0.08 0.31 0.81
Average_Distance Empty cell 1 0.00 0.01 0.81
Peak_Hour Empty cell 1 0.00 0.00 0.40
Weekday Empty cell 1 -0.01 0.01 0.22
Phase2_Count Empty cell 1 -0.05 0.02 0.00

TTR Ratings Statement 4: Overall, the information I received from the Transportation Study Resource was useful

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' agreement with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 53. Model results – travel time reliability rating: information useful.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 2.08 0.73 0.00
Intercept 2 1 2.76 0.74 0.00
Location Columbus 1 0.04 0.26 0.87
Location Houston 1 -0.14 0.27 0.59
Treatment_Assembly Assembly A 1 -0.24 0.16 0.13
Treatment_Mode 511 access 1 -0.53 0.20 0.01
Treatment_Mode App access 1 0.12 0.19 0.52
Gender Female 1 0.03 0.16 0.86
Education Bachelor degree 1 -0.44 0.21 0.04
Education Graduate/Professional degree 1 -0.76 0.24 0.00
Income $100,000 or more 1 -0.25 0.28 0.38
Income $50,000-$99,999 1 0.20 0.29 0.48
Age 25-44 1 -0.66 0.39 0.09
Age 45-64 1 -0.43 0.40 0.28
Age 65 or older 1 -0.10 0.71 0.88
Employment Full-time employed 1 0.57 0.28 0.04
Average_Distance Empty cell 1 0.00 0.00 0.65
Peak_Hour Empty cell 1 0.00 0.00 0.21
Weekday Empty cell 1 -0.01 0.01 0.44
Phase2_Count Empty cell 1 -0.04 0.01 0.00

TTR Ratings Statement 5: In General, Information from the Transportation Study Resource Helped me Reduce my Travel Time

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' agreement with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 54. Model results – travel time reliability rating: information helped reduce travel time.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 0.60 0.69 0.39
Intercept 2 1 1.72 0.69 0.01
Location Columbus 1 -0.16 0.27 0.55
Location Houston 1 -0.11 0.27 0.70
Treatment_Assembly Assembly A 1 -0.02 0.16 0.91
Treatment_Mode 511 access 1 -0.08 0.21 0.70
Treatment_Mode App access 1 0.42 0.19 0.03
Gender Female 1 -0.23 0.17 0.17
Education Bachelor degree 1 -0.43 0.21 0.04
Education Graduate/Professional degree 1 -0.69 0.24 0.00
Income $100,000 or more 1 -0.47 0.27 0.09
Income $50,000-$99,999 1 -0.20 0.27 0.46
Age 25-44 1 -0.11 0.35 0.75
Age 45-64 1 -0.12 0.37 0.74
Age 65 or older 1 -0.14 0.71 0.85
Employment Full-time employed 1 0.16 0.28 0.55
Average_Distance Empty cell 1 0.00 0.00 0.87
Peak_Hour Empty cell 1 0.00 0.00 0.13
Weekday Empty cell 1 0.00 0.01 0.54
Phase2_Count Empty cell 1 -0.04 0.01 0.00

TTR Ratings Statement 6: In General, Information from the Transportation Study Resource Helped me Avoid Congestion

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' agreement with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 55. Model results travel time reliability rating: helped to avoid congestion.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 0.42 0.69 0.54
Intercept 2 1 1.26 0.69 0.07
Location Columbus 1 -0.07 0.26 0.80
Location Houston 1 0.02 0.27 0.93
Treatment_Assembly Assembly A 1 0.01 0.16 0.93
Treatment_Mode 511 access 1 0.03 0.20 0.89
Treatment_Mode App access 1 0.38 0.19 0.05
Gender Female 1 -0.07 0.16 0.68
Education Bachelor degree 1 -0.33 0.20 0.11
Education Graduate/Professional degree 1 -0.39 0.23 0.09
Income $100,000 or more 1 -0.26 0.27 0.34
Income $50,000-$99,999 1 0.06 0.28 0.82
Age 25-44 1 -0.22 0.35 0.53
Age 45-64 1 -0.16 0.36 0.66
Age 65 or older 1 0.25 0.69 0.71
Employment Full-time employed 1 0.18 0.27 0.52
Average_Distance Empty cell 1 0.00 0.00 0.74
Peak_Hour Empty cell 1 -0.01 0.00 0.00
Weekday Empty cell 1 0.00 0.01 0.68
Phase2_Count Empty cell 1 -0.02 0.01 0.06

TTR Ratings Statement 7: Information from the Transportation Study Resource Reduced the Stress of my Trip

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' agreement with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 56. Model results – travel time reliability rating: helped to reduce stress.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 -0.26 0.67 0.70
Intercept 2 1 1.21 0.68 0.07
Location Columbus 1 0.23 0.25 0.37
Location Houston 1 -0.06 0.26 0.81
Treatment_Assembly Assembly A 1 -0.18 0.16 0.25
Treatment_Mode 511 access 1 -0.17 0.20 0.37
Treatment_Mode App access 1 0.04 0.19 0.83
Gender Female 1 -0.09 0.16 0.59
Education Bachelor degree 1 -0.18 0.20 0.36
Education Graduate/Professional degree 1 -0.49 0.23 0.03
Income $100,000 or more 1 -0.40 0.26 0.13
Income $50,000-$99,999 1 0.10 0.27 0.70
Age 25-44 1 0.20 0.35 0.57
Age 45-64 1 0.19 0.36 0.60
Age 65 or older 1 0.53 0.68 0.44
Employment Full-time employed 1 0.12 0.27 0.66
Average_Distance Empty cell 1 0.00 0.00 0.55
Peak_Hour Empty cell 1 -0.01 0.00 0.00
Weekday Empty cell 1 0.00 0.01 0.84
Phase2_Count Empty cell 1 -0.03 0.01 0.02

TTR Ratings Statement 8: Information from the Transportation Study Resource Helped me Plan my Trips

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' agreement with the statement and to account for exogenous factors regarding demographic and trip characteristics.

Table 57. Model results – travel time reliability rating: helped me to plan trips.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 0.34 0.69 0.62
Intercept 2 1 1.18 0.69 0.09
Location Columbus 1 0.06 0.26 0.81
Location Houston 1 0.12 0.26 0.66
Treatment_Assembly Assembly A 1 0.02 0.16 0.90
Treatment_Mode 511 access 1 -0.52 0.20 0.01
Treatment_Mode App access 1 0.07 0.19 0.70
Gender Female 1 0.06 0.16 0.72
Education Bachelor degree 1 -0.40 0.20 0.05
Education Graduate/Professional degree 1 -0.41 0.23 0.07
Income $100,000 or more 1 -0.34 0.27 0.21
Income $50,000-$99,999 1 0.32 0.28 0.24
Age 25-44 1 -0.17 0.36 0.64
Age 45-64 1 0.07 0.37 0.85
Age 65 or older 1 -0.14 0.70 0.85
Employment Full-time employed 1 0.65 0.28 0.02
Average_Distance Empty cell 1 0.00 0.00 0.66
Peak_Hour Empty cell 1 -0.01 0.00 0.02
Weekday Empty cell 1 0.00 0.01 0.65
Phase2_Count Empty cell 1 -0.03 0.01 0.01

Satisfaction with Estimated/Approximate Travel Time

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' satisfaction with the trip experience and to account for exogenous factors regarding demographic and trip characteristics.

Table 58. Model results – satisfaction with estimated travel time.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 1.70 0.79 0.03
Intercept 2 1 2.66 0.79 0.00
Location Columbus 1 0.56 0.27 0.04
Location Houston 1 -0.26 0.27 0.33
Treatment_Assembly Assembly A 1 -0.31 0.17 0.07
Treatment_Mode 511 access 1 -0.27 0.21 0.20
Treatment_Mode App access 1 0.05 0.20 0.80
Gender Female 1 0.08 0.17 0.64
Education Bachelor degree 1 0.34 0.22 0.12
Education Graduate/Professional degree 1 0.04 0.24 0.86
Income $100,000 or more 1 -0.27 0.30 0.36
Income $50,000-$99,999 1 0.32 0.31 0.30
Age 25-44 1 -0.67 0.43 0.12
Age 45-64 1 -0.59 0.44 0.17
Age 65 or older 1 -0.16 0.82 0.85
Employment Full-time employed 1 0.25 0.30 0.40
Average_Distance Empty cell 1 0.00 0.00 0.82
Peak_Hour Empty cell 1 0.00 0.00 0.32
Weekday Empty cell 1 0.00 0.01 0.55
Phase2_Count Empty cell 1 -0.01 0.01 0.29

Satisfaction with Extra Time/Recommended Cushion.

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' satisfaction with the trip experience and to account for exogenous factors regarding demographic and trip characteristics.

Table 59. Model results – satisfaction with the extra time/recommended cushion from travel time reliability.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 1.55 0.73 0.03
Intercept 2 1 2.98 0.74 <0.005
Location Columbus 1 0.11 0.26 0.66
Location Houston 1 -0.24 0.27 0.38
Treatment_Assembly Assembly A 1 -0.29 0.16 0.07
Treatment_Mode 511 access 1 -0.27 0.20 0.18
Treatment_Mode App access 1 -0.03 0.19 0.88
Gender Female 1 0.16 0.17 0.33
Education Bachelor degree 1 -0.17 0.21 0.42
Education Graduate/Professional degree 1 -0.38 0.24 0.11
Income $100,000 or more 1 -0.29 0.28 0.30
Income $50,000-$99,999 1 0.25 0.29 0.39
Age 25-44 1 -0.26 0.38 0.49
Age 45-64 1 -0.16 0.39 0.68
Age 65 or older 1 -0.04 0.72 0.95
Employment Full-time employed 1 0.05 0.28 0.87
Average_Distance Empty cell 1 0.00 0.00 0.42
Peak_Hour Empty cell 1 0.00 0.00 0.47
Weekday Empty cell 1 0.00 0.01 0.58
Phase2_Count Empty cell 1 -0.02 0.01 0.21

Satisfaction with Recommended/Suggested Departure Time

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' satisfaction with the trip experience and to account for exogenous factors regarding demographic and trip characteristics.

Table 60. Model results – satisfaction with the recommended departure time.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 1.25 0.72 0.08
Intercept 2 1 2.71 0.73 0.00
Location Columbus 1 0.04 0.27 0.89
Location Houston 1 -0.13 0.27 0.64
Treatment_Assembly Assembly A 1 -0.24 0.16 0.15
Treatment_Mode 511 access 1 -0.51 0.20 0.01
Treatment_Mode App access 1 -0.12 0.20 0.53
Gender Female 1 0.03 0.17 0.87
Education Bachelor degree 1 -0.24 0.21 0.25
Education Graduate/Professional degree 1 -0.38 0.24 0.11
Income $100,000 or more 1 -0.19 0.28 0.50
Income $50,000-$99,999 1 0.37 0.29 0.20
Age 25-44 1 -0.52 0.38 0.18
Age 45-64 1 -0.64 0.39 0.10
Age 65 or older 1 -0.97 0.70 0.17
Employment Full-time employed 1 0.30 0.28 0.28
Average_Distance Empty cell 1 0.00 0.00 0.77
Peak_Hour Empty cell 1 -0.01 0.00 0.01
Weekday Empty cell 1 0.00 0.01 0.70
Phase2_Count Empty cell 1 -0.02 0.01 0.17

Satisfaction with Total Travel Time Estimate for Most/Majority of the Time

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' satisfaction with the trip experience and to account for exogenous factors regarding demographic and trip characteristics.

Table 61. Model results – satisfaction with total travel time.
Parameter Level DF Estimate Standard Error P-Value
Intercept 1 1 0.74 0.74 0.31
Intercept 2 1 1.81 0.74 0.01
Location Columbus 1 0.38 0.27 0.16
Location Houston 1 -0.31 0.27 0.25
Treatment_Assembly Assembly A 1 -0.12 0.17 0.48
Treatment_Mode 511 access 1 -0.17 0.20 0.39
Treatment_Mode App access 1 0.23 0.20 0.25
Gender Female 1 0.24 0.17 0.16
Education Bachelor degree 1 0.11 0.22 0.61
Education Graduate/Professional degree 1 0.01 0.24 0.97
Income $100,000 or more 1 -0.28 0.28 0.33
Income $50,000-$99,999 1 0.40 0.30 0.18
Age 25-44 1 -0.31 0.39 0.43
Age 45-64 1 -0.17 0.40 0.67
Age 65 or older 1 0.00 0.76 1.00
Employment Full-time employed 1 0.15 0.29 0.59
Average_Distance Empty cell 1 0.00 0.00 0.34
Peak_Hour Empty cell 1 -0.01 0.00 0.08
Weekday Empty cell 1 0.00 0.01 0.67
Phase2_Count Empty cell 1 -0.02 0.01 0.17

Satisfaction with Trips while Using the Transportation Study Resource

Ordinal logistic regression modeling was applied to quantify the impacts of lexicon and information channel in participants' satisfaction with the trip experience and to account for exogenous factors regarding demographic and trip characteristics.

Table 62. Model results – satisfaction on the trips with travel time reliability resources.
Parameter Parameter DF Estimate Standard Error P-Value
Intercept 1 1 2.90 0.82 0.00
Intercept 2 1 4.24 0.83 <0.005
Location Columbus 1 0.07 0.28 0.80
Location Houston 1 -0.65 0.28 0.02
Treatment_Assembly Assembly A 1 -0.15 0.17 0.37
Treatment_Mode 511 access 1 -0.07 0.21 0.74
Treatment_Mode App access 1 0.14 0.20 0.49
Gender Female 1 0.01 0.17 0.96
Education Bachelor degree 1 -0.07 0.23 0.76
Education Graduate/Professional degree 1 -0.51 0.25 0.04
Income $100,000 or more 1 -0.08 0.30 0.79
Income $50,000-$99,999 1 0.17 0.31 0.59
Age 25-44 1 -0.49 0.43 0.26
Age 45-64 1 -0.33 0.44 0.45
Age 65 or older 1 -1.44 0.73 0.05
Employment Full-time employed 1 0.11 0.31 0.72
Average_Distance Empty cell 1 -0.01 0.00 0.03
Peak_Hour Empty cell 1 -0.01 0.00 0.01
Weekday Empty cell 1 -0.01 0.01 0.44
Phase2_Count Empty cell 1 -0.02 0.01 0.07
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