Daily doses were re-expressed as oral morphine equivalents using the conversion factors shown in Table 2. To determine the behavior of opioid dose over time, mean, median dosage, interquartile range and 95th percentile of opioid dose over 6-month periods from the index date were calculated.
Firstly, we did not assess the level of asthma control, which is one of the factors shown to predict the use of health care resources [ 49].
Comparing participating homes using these factors showed that intervention and control homes were comparable, with the exception of the percentage of use of incontinence pads which was slightly higher in the control homes (100% vs. 89% of the homes).
The characteristics shown in this table have been included in a multivariable model using stepwise logistic regression if the factors showed increased or reduced risk from an unadjusted analysis (table 4).
Multivariable adjustment was conducted using all factors shown in Table 3 with the exception of maternal age group (excluded due to fewer than 10 women in some age groups with spontaneous perineal trauma).
In order to find independent prognostic factors as regards DFS, we carried out multivariate analysis using the significant prognostic factors shown in Table 3A.
Response weights were defined as the inverse probability of responding once sampled and were generated using factors shown empirically to predict response (sex, rank, age).
The motion of the thermostatic atoms is therefore scaled using the velocity scaling factor (shown in equation 2) to incorporate the dissipation of heat in the simulation.
However, when oblique rotation was used, the factor correlation matrix (see Table 1) showed two factors, (factors 1 and 3), with a correlation of −.43.
Predictions of buckling knockdown factors using the SPLA approach showed advantages over the use of eigenmodes as the SPLA approach provides a clear design point and does not require experimental data for calibration.
