As regards the remaining cases, the evaluative pattern for case PU (young woman with severe heredity for CHD) could be interpreted in a similar way, with the patient's (young) age as an argument against drug treatment, whereas case GM (diabetic case) did not invite any such interpretation.
Obviously, these focusing patterns for cases of σ = 0.4 and σ = 0.7 are almost the same except the slight variation of foci intensity.
However, all three methods are at least suggestive of significantly different spatial patterns for cases and controls when applied to the 20 year latency data set.
Different migration patterns for cases and noncases before 1970 would imply differential misclassification, but we consider this unlikely because of the long time span between the period of unknown migrations (before 1970) and time of diagnosis for the cancer cases (after inclusion between 1994 and 1997).
The second level analysis involved determining the continued growth patterns for case study children.
However, this realistic compromise 1) is a marked improvement over the current practice to display only county-based spatial patterns for case counts or incidence; 2) incurs only minimal added time and cost for the public health community; and 3) can be implemented, especially for census tracts, with minimal concerns regarding patient privacy.
The pattern for ambulatory cases was similar but not statistically significant.
The pattern we observed with effect modification should not be taken as illustrative of the expected bias pattern for all cases.
We re-examine that dataset using the novel technique of logical analysis of data (LAD), with the double objective of discovering patterns characteristic for cases with good or poor outcome, using them for accurate and justifiable predictions; and deriving novel information about the role of genes, the existence of special classes of cases, and other factors.
The results show strangely systematic behavior of the flow pattern for the case of SPS, which gets distorted for multipoint sparger.
