Skip to main content
. 2020 Mar 26;13:633–648. doi: 10.2147/JPR.S237056

Table 3.

Multilevel Logistic Regression Model Predicting PAINAD Above Cut-off (MMSE 0–9)

Random Intercept Multilevel Logistic Regression Modela for PAINAD Null Model Resident and Nursing Home-Level Model
OR [CI] p OR [CI] p
Fixed model part
Interceptb 0.33 (0.22) 0.129 2.01 (1.86) 0.281
Time × group 0.89 [0.46–1.72] 0.724
Resident-level
Resident characteristics
 Gender (ref.: female) 0.77 [0.44–1.35] 0.360
 Age 1.01 [0.96–1.05] 0.885
 Mini-Mental State Examination 0.92 [0.86–0.99] 0.034
Diagnoses
 Dementia (ref.: not present) 0.76 [0.46–1.27] 0.292
 Depression (ref.: not present) 1.34 [0.64–2.82] 0.443
 Musculoskeletal (ref.: not present) 1.08 [0.58–1.99] 0.814
 Neuropathies (ref.: not present) 1.55 [0.28–8.56] 0.612
 Tumor (ref.: not present) 1.29 [0.69–2.43] 0.417
Secondary outcomes
 Neuropsychiatric Inventory Index 1.06 [0.91–1.23] 0.440
Nursing home-level
 Size in terms of resident care places 0.99 [0.98–1.01] 0.440
 Number of registered practical nurses 0.94 [0.89–0.99] 0.049
 Number of nursing assistants 1.05 [0.99–1.12] 0.123
Random model part
Nursing home-levelb 0.45 (0.30) 0.136 0.15 (0.24) 0.545
ICCc 0.1201 0.0430
−2LL 1155.68 1008.21
Sample size, nursing homes 15 15
Sample size, residents 268 222

Notes: aRobust covariance method; baverage log-odds (SE, standard error); clatent variable approach. Bold font indicates statistical significance (p<0.05).

Abbreviations: PAINAD, Pain Assessment in Advanced Dementia; OR, odds ratio; CI 95%, confidence interval; p, p-value; ref, reference; ICC, intraclass correlation coefficient; −2LL, log-likelihood ratio.