tag:blogger.com,1999:blog-621640681266100373.post4782005576183632186..comments2018-07-18T09:31:26.458-04:00Comments on Independent Investigation of Truth: RadiationNetwork vs NETC CPM ComparisonJames J Keene PhDhttp://www.blogger.com/profile/17926197110377297689noreply@blogger.comBlogger1125tag:blogger.com,1999:blog-621640681266100373.post-1208831863578603142015-10-23T03:59:47.547-04:002015-10-23T03:59:47.547-04:00How to use both RadiationNetwork (RN) and NETC dat...How to use both RadiationNetwork (RN) and NETC data in studies of radiation levels? This methodological question is important because investigators like to have the largest samples possible which enables statistical analysis to reveal smaller effects, which might nonetheless be important scientifically or health-wise. Two quite different approaches might be suggested.<br /><br />Based on the present pilot study above, four categories of radiation sensors may be identified;<br />1. RN "Std" Geiger counters mostly made by seintl.com (SI).<br />2. RN "Pancake" Geiger counters.<br />3. NETC "Std" Geiger counters mostly made by gqelectronicsllc.com (GQ).<br />4. NETC "EPA beta" counters.<br /><br />Option 1: z scores. A z score is a data standardization method where each member of a group of numbers (CPM) is processed by subtracting the group average (mean) and then dividing by the group standard deviation. Thus, the group average z score is zero. A z score of 1.5 indicates a value 1.5 standard deviations above the average within that group, and so on.<br /><br />The z score option would allow combining the four groups of CPM counters listed above. In this case, differences between the groups would be lost, but relatively high and low CPM value variation would be included in any subsequent analysis.<br /><br />Option 2: CPM calibration. This option would not suffer the disadvantage of Option 1, where between-group variability is lost.<br /><br />1. Pick an arbitrary group from the 4 listed above to be a "baseline group".<br />2. "Calibrate" or "adjust" the CPM of the other three groups to our arbitrary baseline group as in the following example.<br /><br />Example:<br />1. Pick the CQ Std NETC units as our baseline group.<br /><br />2a. Since the baseline average CPM is about 1.44 times greater (19.59 / 13.58) than the SI Std RN unit CMPs, according to the data reported above, each of these values would be multiplied by 1.44 to be comparable to our baseline group and aggregated with it.<br /><br />2b. The SI Pancake RN units reportedly averaged CPMs 2.85 times greater than the SI Std RN units. Thus, these values would be divided by 2.85 and then multiplied by 1.44 to be added to our baseline group (or simply multiplied by 0.505, which equals 1.44 / 2.85).<br /><br />2c. The average of all of the EPA beta NETC monitors can be computed and used to adjust those CPM values to our baseline group in a similar manner.<br /><br />Option 2 has the advantage of inclusion of both within-group variation and between-group variation in CPM values allowing more comparisons as a function of other variables such as location, time, etc. The weakness of Option 2 is the validity of conclusions depends on accuracy of the calibration factors used. This accuracy would increase as the present pilot study is replicated a number of times to home in on a stable set of reliable calibration factors.<br />James J Keene PhDhttps://www.blogger.com/profile/17926197110377297689noreply@blogger.com