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Table 4 Correlations among CREDI, Bayley-III, and the ASQ-3

From: Reliability and validity of the Caregiver Reported Early Development Instruments (CREDI) in impoverished regions of China

 

Bayley III (n = 248)

    
 

Cognitive

RC

EC

Fine Motor

Gross Motor

    

CREDI

    

 Cognitive

0.835***

0.791***

0.814***

0.828***

0.864***

    

 Language

0.889***

0.855***

0.897***

0.870***

0.852***

    

 Motor

0.879***

0.813***

0.839***

0.872***

0.901***

    

 Social-emotional

0.868***

0.803***

0.831***

0.856***

0.896***

CREDI (n = 946)

 

ASQ-3

Cognitive

Language

Motor

Social-emotional

 Problem Solving

−0.100+

− 0.017

− 0.053

−0.069

− 0.117*

0.116***

0.060+

0.059+

0.059+

 Communication

0.319***

0.404***

0.426***

0.322***

0.249***

0.388***

0.472***

0.348***

0.362***

 Fine Motor

−0.181**

−0.134*

− 0.145*

− 0.167**

− 0.171**

0.060+

− 0.016

0.009

− 0.002

 Gross Motor

0.429***

0.373***

0.391***

0.426***

0.549***

0.491***

0.442***

0.533***

0.484***

 Personal-Social

−0.036

0.047

0.031

−0.011

0.016

0.196***

0.133***

0.153***

0.149***

  1. *** p < 0.001, ** p < 0.01, *p < 0.05, + p < 0.1
  2. Note: Pearson correlations on internally standardized scores. Since raw scores are increasing in age, we eliminated the age effect by internally standardizing raw scores within age (month) groups. This is done by computing age-adjusted z-scores using age-conditional means and standard deviations estimated by non-parametric regression. Compared to parametric procedures, the advantage of this non-parametric standardization method is less sensitive to outliers and small sample size within age category and yields normally distributed standardized scores with mean zero across the age range (in months) ([2] [22];). Standard Errors (SE) computed using bootstrap method. Bootstrapping allows estimation of the sampling distribution of almost any statistic using random sampling methods. Bootstrap is asymptotically more accurate than the standard intervals obtained using sample variance and assumptions of normality. RC Receptive Communication, EC Expressive Communication