Table 4.
Correlations among Composites* | ||||||||
---|---|---|---|---|---|---|---|---|
Reliability Hospital-Level† | Alpha‡ | 1 | 2 | 3 | 4 | 5 | 6 | |
1 - Nurse Communication | 0.89 | 0.86 | ||||||
2 - Doctor Communication | 0.76 | 0.88 | 0.61 | |||||
3 - Responsiveness | 0.89 | 0.72 | 0.88 | 0.57 | ||||
4 - Physical Environment | 0.88 | 0.51 | 0.75 | 0.55 | 0.85 | |||
5 - Pain Control | 0.80 | 0.83 | 0.70 | 0.56 | 0.74 | 0.65 | ||
6 - Medicine Communication | 0.66 | 0.67 | 0.62 | 0.53 | 0.65 | 0.64 | 0.57 | |
7 - Discharge Information | 0.88 | 0.51 | 0.43 | 0.41 | 0.42 | 0.22 | 0.24 | 0.61 |
Correlations among composites (factors) come from the SEM analysis
For these calculations, the number of respondents is assumed to be 300 (that required for power at the hospital-level) however, skip patterns require that the sample will be less than 300 for some items. Therefore the sample size for each item is estimated by multiplying 300 by the proportion observed to respond to that item
Cronbach's coefficient (1951) is an estimate of internal consistency reliability