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Table 4 Results of mixed-effects logistic regression models with SIC proportion scores by phase and stage predicting program start-up status

From: The relative value of Pre-Implementation stages for successful implementation of evidence-informed programs

Outcome

Model

Predictor

 

Fixed effects

 

Variance componentsb,c

 

β

SE

p

95% CI

 

Var

SE

Start-Upd

          
 

Phase 1

         
  

Intercept

 

-1.73

0.74

.019

[-3.17, -0.29]

 

8.86

3.83

  

Proportiona

 

13.78

1.10

 < .001

[11.63, 15.94]

   
 

Stage 1

         
  

Intercept

 

-0.97

1.09

.373

[-3.10, 1.16]

 

8.70

6.08

  

Proportiona

 

8.33

3.39

.014

[1.68, 14.98]

 

63.19

59.55

 

Stage 2

         
  

Intercept

 

-1.51

0.38

 < .001

[-2.25, -0.77]

 

1.92

0.87

  

Proportiona

 

7.87

0.47

 < .001

[6.94, 8.79]

   
 

Stage 3

         
  

Intercept

 

-1.23

0.83

.139

[-2.87, 0.40]

 

11.98

5.23

  

Proportiona

 

13.33

1.11

 < .001

[11.16, 15.50]

   

Competencee

        
 

Phases 1 & 2

        
  

Intercept

 

-4.53

0.45

 < .001

[-5.41, -3.65]

 

1.1138

0.7959

  

Phase 1a

 

3.07

0.83

 < .001

[1.46, 4.69]

   
  

Phases 1 × 2a

 

8.22

1.42

 < .001

[5.45, 11.00]

   
  1. aProportion scores range from 0.00 to 1.00 and were grand mean centered prior to entry, thus the intercept reflects the log-odds of program start-up for an average proportion in the respective phase or stage
  2. bSite-level variance component estimates are not available for the Bernoulli outcome distribution and, as such, the reported estimates are limited to program-level variance
  3. cVariance components for the proportion predictor specified based on the likelihood ratio test
  4. dThe sample for this regression include N = 1287 sites with a known end-status (discontinued or achieved start-up) for program start-up
  5. eThe sample for this regression include N = 1105 sites with a known end-status (discontinued or achieved competence) for competency