Ron! It would require me to draw pictures with explanations....just draw a bunch of circles that represent every person in a population and then make sure each circle crosses over another circle it has things common with but, the circle is free of those things not common with the original circle. Then, look at all the circles and how each crosses over with other circles - the parts of the circle that are not overlapping with another circle represents unique variables for each person in the population. Then calculate the space that each circle has free versus each part of the circle that overlaps with other circles. That is your multivariate picture of how much is similar and fifferent for each circle. The thing is that you choose all those variables you listed previously as well as any and all variables that people have. You would eventually see the unique portion of each circle minimize into something that probably is not significant in the outcome you wish to acheive with that particular individual. Get it?
________________________________ From: [EMAIL PROTECTED] on behalf of Ron Carson Sent: Thu 8/3/2006 2:46 PM To: Lehman, David Subject: Re: [OTlist] FW: Interesting Stats WAY, WAY, WAY, over my head. David, please decipher!!! Ron ----- Original Message ----- From: Lehman, David <[EMAIL PROTECTED]> Sent: Monday, July 31, 2006 To: [email protected] <[email protected]> Subj: [OTlist] FW: Interesting Stats LD> Ron...from our buddy Dan...have fun with this one. LD> ________________________________ LD> From: Lofald, Dan [mailto:[EMAIL PROTECTED] LD> Sent: Mon 7/31/2006 2:00 PM LD> To: Lehman, David; Ron Carson LD> Subject: RE: [OTlist] Interesting Stats LD> Howdy David, Howdy Ron LD> We might not be sitting at the lunch table but the good conversation continues. LD> As the Irish saying goes, "Is this a private fight or can anyone join" LD> It appears to be that there are about 6 different concepts in play. LD> David's comments about taking all of the variables en' mass LD> and seeing what regression would tell us. LD> Yep-folks do this all of the time. For example, I was LD> involved trying to find lead indicators of newborn deaths at Univ. LD> of Florida Hospital. There were 1400 independent variables and 1 LD> dependent variable (death/life). LD> We hunted around for months looking for best predictive sets LD> of predictors. The approach to this work was, "if it works, it LD> works." However, this is nothing more than mainframe level data LD> grubbing. It can never tell us anything scientifically definitive LD> because the alpha level is astronomical. However, it might give LD> insight on a place to look with tools that are more sophisticated. LD> Invariably, meaningful finds with first-order relationships LD> are rare events. The good stuff is going to emerge out of finding LD> important suppressor and mediator variables at work. In addition, LD> most of the variables will probably not be in a linear LD> relationship with each other (especially not with human beings). LD> With regression, you can check for suppressor and mediator LD> variables and you can test polynomial solutions --- however-to get LD> to the good stuff, we would probably have use multi-variate tools. LD> At the broader level - the two of you have an ontological & LD> mathematical conversation combined (I love it). LD> Let's look at the passage, "All humans are unique." What LD> does that statement mean? Every part of every human is unlike LD> every part of every other human? If that were the case, and we LD> used Set Theory, we would have 121 billion non-intersecting LD> circles. If that were the case, not only would science be LD> impossible, but so also preclude the possibility of language and LD> culture. LD> If by, "All humans are unique," we mean, that some part of my LD> circle does not overlap with your circle - we are now onto LD> something important. Now we can ask how much of our two Venn LD> circles overlap and do not overlap. This is expression we have LD> with a Pearson product-moment correlation of p = .80, which means LD> that 64% of the variance in one variable can be predicted by the LD> variance of the other circle. LD> But what happens when there are ten of us. How do our LD> circles overlap now (we are talking about the ephemeral LD> phenomological/psychological variables that you guys are talking LD> about). If we look at enough people can we find patterns among LD> what initially appeared discretely idiosyncratic? LD> [[Oh gee - I cannot finish this response this week but I LD> should would like to take it up with you guys another time. You LD> are drilling down to one of the most interesting and important LD> pieces of social science. LD> Dan LD> Daniel R. Lofald, PhD LD> Staff Development Coordinator LD> Chippewa Valley Technical College LD> 620 W. Clairemont Ave., Eau Claire, WI 54701-6162 LD> Phone 715-852-1328 Fax 715-833-6451 LD> ________________________________ LD> From: Lehman, David [mailto:[EMAIL PROTECTED] LD> Sent: Wednesday, July 26, 2006 8:54 PM LD> To: Lofald, Dan LD> Subject: FW: [OTlist] Interesting Stats LD> Ron remembers you.....well! LD> More thoughts? LD> ________________________________ LD> From: [EMAIL PROTECTED] on behalf of Ron Carson LD> Sent: Wed 7/26/2006 8:42 PM LD> To: Lehman, David LD> Subject: Re: [OTlist] Interesting Stats LD> Given that you have a PhD, and if I remember, you and Dan L. LD> frequently talked about this stuff, I feel that I am definitely LD> out-classed!! <lol>. But, being the brave, (uh, stupid) person that I LD> am, I will continue wading in the deep end of the pool. LD> It seems that regression analysis looks at individual variables. But LD> we know that people are not just collection of individual variables. LD> We are after all, greater then the sum of our parts. LD> How does regression analysis look at the SUM of the variables? LD> Also, is it possible to quantify a subjective feeling? I know this is LD> done with pain scales, but the subjective nature of such scales LD> renders them almost useless for comparisons sake. In other words, my LD> reported pain of 9 is total meaningless when COMPARED to your reported LD> pain of 9. LD> Lastly, just because someone has a history of any of the variables, in LD> and of itself, that history is meaningless. For example, just because LD> someone has a history of total hip arthroplasty, that doesn't mean LD> they will need adaptations to dress their lower body. LD> Ok, one more "lastly". You said: david>> The more variables, the more chances for your results occuring david>> because of poor internal validity LD> Are you saying that the greater the number of variables, the less LD> likely you can predict the results? If so, they I maintain that the LD> number of variable affecting patient outcomes is infinite and thus you LD> can never truly predict the outcomes. Keep in mind that I refer to LD> patients, not to procedures. LD> Ron LD> ----- Original Message ----- LD> From: Lehman, David <[EMAIL PROTECTED]> LD> Sent: Wednesday, July 26, 2006 LD> To: [email protected] <[email protected]> LD> Subj: [OTlist] Interesting Stats LD>> I am not surprised you disagree, Ron! Thats what makes us get along so well! LD>> I think you walked right into what I wanted to get across: LD>> Each of the variables you listed below can be measured, LD>> right? If something (a dependent or attribute variable) can be LD>> measured, then it has a number which can then be used to determine LD>> if the unique variable is significant , and this is the important LD>> part, I think, that when using a regression analysis, it takes LD>> into account all the other unique and not unique variables thought LD>> to be a contributor to the healing (increased functional LD>> activities, increased occupation). LD>> So, if one individual, has a history of any or most of these, LD>> then how does that effect your treatment versus if she had 30% LD>> relevant, or 10% relevant, etc... The more variables, the more LD>> chances for your results occuring because of poor internal LD>> validity (poor job controlling all the other variablesvariables) - LD>> and you dont know if it were treatment approach a or b or c or d LD>> or e.....or placebo. LD>> OK...I am going statistical here and trying to explain LD>> it..,.....but, if you can quantify something, you can study its LD>> relationship with other variables and outcomes. LD>> This is fun. LD>> ________________________________ LD>> From: [EMAIL PROTECTED] on behalf of Ron Carson LD>> Sent: Wed 7/26/2006 7:31 PM LD>> To: Lehman, David LD>> Subject: Re: [OTlist] Interesting Stats LD>> Hello David: LD>> I hate to disagree but every person has unique variables. That's what LD>> makes us unique. And perhaps the greatest and uniqueness variable of LD>> all is the subjective feeling and experiences associated with injury, LD>> disease and illness. It is in fact that subjective experience of our LD>> patient's that makes being an OT so difficult. LD>> Regarding a list, here's a few: LD>> age, gender, marital status, employment history, race, religion, LD>> medical history, current medications, spiritual beliefs, family LD>> support, financial support, cognitive status, mental status, LD>> education, prior experience with OT, expectations, diet, sleep LD>> patterns, do they have regular bowel movements, etc. LD>> The list is truly endless!! LD>> This is a GREAT topic LD>> Ron LD>> ----- Original Message ----- LD>> From: Lehman, David <[EMAIL PROTECTED]> LD>> Sent: Wednesday, July 26, 2006 LD>> To: [email protected] <[email protected]> LD>> Subj: [OTlist] Interesting Stats LD>>> I mis-spoke, perhaps....meaning that there really are no LD>>> unique variables that ONLY exist to one person on earth. If LD>>> enough data is gathered on a population, the "unique" or should I LD>>> say less appearing variables we call unique, would be detectable LD>>> and the statistical model would show us what contribution that LD>>> particular "unique variable" makes and if it is significant in the LD>>> outcome. LD>>> I guess my next question would be to ask the members to list LD>>> variables they consider unique to a person that have an impact on LD>>> the treatment they provide. LD>>> ________________________________ LD>>> From: [EMAIL PROTECTED] on behalf of Ron Carson LD>>> Sent: Wed 7/26/2006 4:04 PM LD>>> To: Lehman, David LD>>> Subject: Re: [OTlist] Interesting Stats LD>>> I don't know much, if anything, about regression theory, but I'm LD>>> pretty confident that it is impossible to take into account ALL the LD>>> UNIQUE variables that account for healing. Also, it seems rather LD>>> counterintuitive to try include a "unique" variable into a "general" LD>>> logarithm. LD>>> Ron LD>>> ----- Original Message ----- LD>>> From: Lehman, David <[EMAIL PROTECTED]> LD>>> Sent: Wednesday, July 26, 2006 LD>>> To: [email protected] <[email protected]> LD>>> Subj: [OTlist] Interesting Stats LD>>>> all of the unique variables of LD>>>> a client could one day be analysed in a regression model LD>>>> and thus determine how much these LD>>>> unique variables actually account for healing, then LD>>>> include them in the logaritm? LD>>> -- LD>>> Unsubscribe? LD>>> [EMAIL PROTECTED] LD>>> Change options? LD>>> www.otnow.com/mailman/options/otlist_otnow.com LD>>> Archive? LD>>> www.mail-archive.com/[email protected] LD>>> Help? LD>>> [EMAIL PROTECTED] LD>> -- LD>> Unsubscribe? LD>> [EMAIL PROTECTED] LD>> Change options? LD>> www.otnow.com/mailman/options/otlist_otnow.com LD>> Archive? LD>> www.mail-archive.com/[email protected] LD>> Help? LD>> [EMAIL PROTECTED] LD> -- LD> Unsubscribe? LD> [EMAIL PROTECTED] LD> Change options? 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