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Table 1 Linear regression analyses to investigate how well relative quintiles, actual mean wealth index scores and absolute income (per quintile) predict SBA coverage (N = 1465 observations)

From: Absolute income is a better predictor of coverage by skilled birth attendance than relative wealth quintiles in a multicountry analysis: comparison of 100 low- and middle-income countries

  SBA prevalence (coefficients expressed as percent point)
Analysis level Cross-country analysis Within country analysis  
  Model 1 Model2 Model 3 Model 4 Model 5 Model 6 Model 7
Asset quintile 1 0 (reference) p < 0.001    0 (reference) p < 0.001    0 (reference) p = 0.139
Asset quintile 2 10.19 (1.05)    10.19 (1.17)    2.18 (3.93)
Asset quintile 3 18.66 (1.80)    18.66 (2.02)    5.36 (6.53)
Asset quintile 4 28.60 (2.23)    28.60 (2.49)    9.98 (9.23)
Asset quintile 5 40.04 (2.56)    40.04 (2.86)    11.79 (14.02)
Mean wealth scores   6.97 (1.82)
P < 0.001
   6.85 (3.29)
P < 0.001
  
Log incomea    19.13 (1.24)
p < 0,001
   18.38 (1.31)
p < 0.001
12.78 (6.13)
p = 0.04
Survey specific intercepts NO NO NO YES YES YES YES
R-squared 0.220 0.128 0.516 0.877 0.777 0,879 0,881
  1. Robust standard errors in parentheses are clustered at the country level
  2. aIncome is expressed in 2011 purchasing power parity-adjusted international dollars. Model 1 and model 4: cross-country and within-country prediction of SBA coverage according to wealth quintiles. Model 2 and model 5: cross-country and within-country prediction of SBA coverage according to actual mean wealth scores. Model 3 and model 6: cross-country and within-country prediction of SBA coverage according to household income. Model 7: within-country prediction of SBA coverage according to wealth quintiles and household income