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Table 6 Determinants of the difference in percent of X houses converted to P between CMC and non-CMC areas of a block*

From: Determinants of performance of supplemental immunization activities for polio eradication in Uttar Pradesh, India: social mobilization activities of the Social mobilization Network (SM Net) and Core Group Polio Project (CGPP)

Variable

Coefficient

Std. Err.

z

p value

[95% Confidence Interval]

(Constant)

12.14412

4.70592

2.58

0.010

2.920682

21.36755

Number of children < 5 years

−.0006623

.0003569

−1.86

0.063

−.0013618

.0000372

District

1

Baghpat (Index)

2

Bareilly

−2.262005

1.151339

−1.96

0.049

−4.518589

−.0054215

3

Mau

6.324774

1.667669

3.79

0.000

3.056204

9.593345

4

Meerut

−10.04491

.8974011

−11.19

0.000

−11.80379

−8.286038

5

Moradabad

−4.138752

1.738614

−2.38

0.017

−7.546373

−.7311312

6

Muzafarnagar

−5.157229

1.138899

−4.53

0.000

−7.389431

−2.925028

7

Rampur

−7.979791

.4193138

−19.03

0.000

−8.801630

−7.157951

8

Saharanpur

−9.242826

1.04674

−8.83

0.000

−11.29440

−7.191252

9

Shahjahanpur

2.645487

2.01286

1.31

0.189

−1.299647

6.590620

 

Sitapur

−1.617467

3.03375

−0.53

0.594

−7.563508

4.328574

Number of Mosque Announcements (Quartile, Percentile)

1

< 25th

(Index)

2

25–50th

3.280323

1.684365

1.95

0.051

−.020971

6.581618

3

50-75th

4.814767

1.924814

2.50

0.012

1.042201

8.587334

4

> 75th

4.742434

2.12667

2.23

0.026

.5742373

8.910632

Number of Bullawa Tollies (Quartile, Percentile)

1

< 25th

(Index)

2

25–50th

.1520856

.8256602

0.18

0.854

−1.466179

1.770350

3

50-75th

1.929366

1.24142

1.55

0.120

−.5037729

4.362504

4

> 75th

3.365150

1.794372

1.88

0.061

−.1517546

6.882054

Variance of fixed effects:

43.142147

6.7934335

    

Variance of random effects

14.77656

5.8608284

    
  1. * Coefficients and standard errors adjusted for differences between Blocks and changes within Block values over time (time-varying covariate values at the Block level) by using a Generalized Linear Latent And Mixed Model (GLLAMM).