Maternal characteristics of deliveries before arrival to hospital in Bisha, Saudi Arabia

This is a case control retrospective study [unpaired design] carried out at Prince Abdulla Hospital in Bisha, Saudi Arabia on all 1800 newborn deliveries between January to December 1992. During this period 43 [2.4%] babies were born before arrival to hospital. This is 5 times the figures quoted for some western countries. Most of the deliveries occurred at night. There was no age or parity difference between the women who delivered before arrival and the control group. The conditions associated with high mortality among these women include retained placenta, shock, postpartum haemorrhage and acute inversion of the uterus. In conclusion, birth before arrival at hospital remains a significant problem in Bisha region of Saudi Arabia

impact of removing outliers in principal component analysis: a Monte Carlo study

Based on Bahnassys work [1989] to detect outliers in Principal Component Analysis; a simulation study has been conducted to explore the effect of removing outliers in Principal Component Model. Bahnassy's method mentions that if variables are standardized, the Pearson product moment correlation equals the average of the cross products. For each observation, the average over the [p[p-l]/2] correlations of the deviation squared of its cross products from the elements of the correlation matrix was computed. Observations with large deviations [D[k]] are defined as outliers. This method was applied to simulated data sets from normal distributions and from distributions with binary variables added. In some instances removing outliers causes the number of eigenvalues greater than one to change and changes the importance of some variables in each factor. Besides, the number of components were changed. These changes depend on number and type of variables sampe size, type of correlation matrix, and number of outliers in the data