**5. Appendix**

As presented in this paper, LVMs are based on the results of the separate models which were presented in Khatab, 2007. At that stage, we have used separate geoadditive probit

Associations Between Nutritional Indicators Using Geoadditive

Latent Variable Models with Application to Child Malnutrition in Nigeria 561

Variable Mean S.dv 10% median 90%

const \* 1.133 0.154 -1.33 -1.133 -0.94

male \* 0.117 0.030 -0.156 -0.117 -0.077

urban 0.032 0.039 -0.020 0.032 0.083 work 0.027 0.033 -0.016 0.025 0.070

trepr \* 0.075 0.039 0.026 0.074 0.128

anvis \* 0.147 0.039 0.095 0.147 0.199

radio 0.017 0.037 -0.030 0.017 0.063

elect \* 0.131 0.039 0.077 0.129 0.180

water 0.044 0.044 -0.008 0.043 0.106 educ -0.543 0.943 -1.766 -0.509 0.606

toilet \* 0.078 0.048 0.013 0.078 0.140

Table A1. Fixed effects of separate model using Bayesian geoadditive model on Stuniting

Variable Mean S.dv 10% median 90%

const \* 0.710 0.121 -0.863 -0.718 -0.551

male \* 0.032 0.022 -0.061 -0.033 -0.004 urban -0.022 0.030 -0.059 -0.023 0.016 work \* 0.044 0.026 0.009 0.043 0.077 trepr 0.014 0.031 -0.027 0.014 0.053 anvis \* 0.079 0.030 0.040 0.080 0.116

radio \* 0.035 0.028 0.0007 0.034 0.072

elect \* 0.065 0.029 0.024 0.067 0.101

water \* 0.046 0.033 0.001 0.047 0.089

educ \* 0.063 0.038 0.013 0.064 0.111

toilet \* 0.105 0.044 0.051 0.106 0.159

Table A2. Fixed effects of separate model using Bayesian geoadditive model on

underweight

models with the binary target variables for diarrhea, cough, and fever using covariate information from the 2003NDHS. The computations for the separate models were carried out using BayesX program (Brezger A, Kneib T, Lang S, 2005). We are showing here the results of Model 3, which was selected from a long hierarchal analysis based on its DIC (the value of deviance information criterion).

Source:Khatab, 2007

Fig. A1. Nonlinear effects of child's age, BMI, and Mother's age at birth using separate Bayesian Gaussian Model children for Nigeria using Bayesian latent variable model for continuous responses.

models with the binary target variables for diarrhea, cough, and fever using covariate information from the 2003NDHS. The computations for the separate models were carried out using BayesX program (Brezger A, Kneib T, Lang S, 2005). We are showing here the results of Model 3, which was selected from a long hierarchal analysis based on its DIC (the

Fig. A1. Nonlinear effects of child's age, BMI, and Mother's age at birth using separate Bayesian Gaussian Model children for Nigeria using Bayesian latent variable model for

value of deviance information criterion).

Source:Khatab, 2007

continuous responses.


Table A1. Fixed effects of separate model using Bayesian geoadditive model on Stuniting


Table A2. Fixed effects of separate model using Bayesian geoadditive model on underweight

Associations Between Nutritional Indicators Using Geoadditive

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Table A3. Fixed effects of separate model using Bayesian geoadditive model on wasting

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Variable Mean S.dv 10% median 90%

const \* 0.041 0.127 -0.214 -0.032 0.116

male 0.026 0.024 -0.005 0.025 0.058 urban -0.051 0.030 -0.111 -0.050 0.006

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Table A3. Fixed effects of separate model using Bayesian geoadditive model on wasting

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