Read more about age-equivalent and other scores in
Thursday, September 21, 2017
Wednesday, September 6, 2017
Recently, a group of us completed a study of clients who saw Christian counselors. We assessed their current well-being using two measures: The Schwartz Outcome Scale (SOS) and the Theistic Outcome Scale (TSOS). (See references below.)
The TSOS was designed by Richards (2005) as a measure of well-being for people associated with a theistic religion like Christianity, Judaism or Islam. We used the 17-item version, which uses a 5-point response format from 1 = never to 5 = almost always to rate each item (e.g., “I felt spiritually alive.”).
We only calculated coefficient alpha, which was strong at .95.
The TSOS was significantly correlated with ratings of satisfaction with Christian counseling (.65) and likelihood of returning to Christian counseling (.62).
It was significantly correlated with the SOS measure of general well-being (.84).
Other significant correlations were:
TIPI (a Big 5 measure; Gosling et al., 2003)
Conscientiousness .39Snyder's Hope Scale .72 (Snyder et al., 2010)
Attachment to God Inventory (Beck & McDonald, 2004)
Religious Practices Index .41 (See Sutton et al., 2016)
Intratextual Fundamentalism Scale .56 (See Williamson et al., 2010)
Counselors, read more about reliability and validity of test scores in APPLIED STATISTICS: CONCEPTS FOR COUNSELORS
Resource Link: A – Z Test Index
Beck, R., & McDonald, A. (2004). Attachment to God: The Attachment to God Inventory, tests of working model correspondence, and an exploration of faith group differences. Journal of Psychology and Theology, 32, 92-103. doi:10.1037/t46035-000
Gosling, S. D., Rentfrow, P. J., & Swann, Jr., W. B. (2003). A very brief measure of the big-five personality domains. Journal of Research in Personality, 37, 504-528. doi:10.1016/s0092-6566(03)00046-1
Read more about validity of surveys and tests in CREATING SURVEYS
Please check out my website www.suttong.com
Also, consider connecting with me on FACEBOOK Geoff W. Sutton
You can read many published articles at no charge:
Sunday, September 3, 2017
In large samples involving thousands of people, and when data are normally distributed (close to the shape of a bell curve), the mean and median will be nearly the same. In fact, in a theoretical distribution called the normal curve, the mean, median, and mode are in the middle.
But, many samples are not normal distributions. Instead, the often contain extreme scores called outliers or a lot of scores bunched up at high or low levels (skewed). Sadly, even people that understand statistics, continue to report the mean as if they are not thinking about their samples.
Suppose you work for a company where the top person earns $300,000 but most folks earn $30,000 to $60,000. Well that $300,000 is gonna skew results and the mean will look much higher than the median.
I ran some fictitious data on a sample of 10 people. Nine earn between $30 and $60K and one earns $300K. The Mean = $67K (standard deviation = 82.58), but the Median is only $38.5K and the Range = $270K.
Now those results are fictitious and it is a small sample so it magnifies the differences. But you know some folks are earning over $1,000,000.00 in some companies and lots of folks aren't earning anywhere near that amount.
So who cares? Well salaries make a lot of difference if you are arguing for a raise, considering a change of jobs, voting on budgets in not-for-profit organizations, and more. How motivating is it to give a donation to a company that helps the poor where the CEO pulls down nearly a million bucks a year and you get by on $65K-- or less?
But there's more. Teacher evaluations are usually skewed -- most students give high ratings-- so the median and range are more appropriate than the mean.
I see research papers where the scientists report the average age of people in surveys is 19 and they tell you thir sample was from a university. No problem with age 19 but when they report a Mean of 19 and a standard deviation of 5, there is a problem! If you understand standard deviations, you will know why they probably did not have a lot of 14-year olds in their university!
You can see that knowledgeable folks can play games with a simple statistic.
If you forgot about the meaning of some terms, here's a link to a free glossary.
A simple example
Counselors, teachers, and parents - think about test scores and how they are reported. Test scores for students at school may be distorted by a few very high scoring or very low scoring students.
"Averages" can be deceiving.
Read more about basic statistics in APPLIED STATISTICS: CONCEPTS FOR COUNSELORS at
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