Repeated measures vs factorial analysis
Hi all. I have a question regarding analysis of data using repeated measures. I can easily analyse the data using a standard, factorial approach (entering each observation as a row in SPSS). However, I can not figure out how to do a repeated measures analysis. The study I am trying to analyse has two factors, A & B, each with two levels. Each subject in the study solved 10 tasks in two combinations of factors, e.g. A1B1 followed by A2B2. Due to the nature of the study, each subject only experienced each level of the factors once (i.e. only one time A1 and one time A2, as in A1B1 followed by A2B2). The ten tasks are specific (i.e. nested within) one of the factors, say B. Now, do I analyse this design based on four groups, one for each combination of A and B, and use contrasts to find the main effects and interaction of A and B? Or is there some other approach? Kindest regards, Kasper Hornbæk = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Sensitivity Analysis
[EMAIL PROTECTED] (Christopher J. Mecklin) wrote in message news:<[EMAIL PROTECTED]>... > Judith, Rich, Art, edstat-l list; > > My thanks to your replies and my apologies for not articulating my question > better in my initial post. To be somewhat less vague about my question > (I'll probably be still a little vague because of my lack of knowledge), > the colleague of mine who asked about "sensitivity analysis" meant the > question in regards to population ecology. To try to be more specific about > a topic that I know little about, an ecologist might be modelling the risk > of extinction. The model will involve several parameters. The use of the > term "sensitivity analysis" in this context apparently means determining > how "sensitive" the model's predictions are to uncertainty in the estimates > of the parameters to help determine what parameters need to be estimated > "more carefully". (These last few sentences were paraphrased from > http://www.ramas.com/pva.htm, a hit I got from a hastily conducted Google > search of "sensitivity analysis ecological model".) > > I was sent a list of references by another reader of this newsgroup that I > passed on to my colleague that he found satisfactory for his purposes. I > suppose I could post that list of references if anyone else is interested. > > The use of this term "sensitivity analysis" is apparently from the use of > the term "sensitivity" in epidemiology (and quite possibly others use of > the term). This seems to be one of those situations where the same word > means different things to different people. > > Again, my apologies for the vague request. > > CJM > > At 11:27 AM 02/06/2002 -0500, Conn, Judith wrote: > >I do know that in epidemiology and medical science the purpose is to find > >out how "sensitive" the test is . This ia what I think of when talking > >sensitivity analysis. Further info can be obtained from P Armitage & G > >Berry, "Statistical Methods in Medical Research", Blackwell Scientific > >Publications. Judy Conn > > > > > -Original Message- > > > From: Rich Ulrich [SMTP:[EMAIL PROTECTED]] > > > Sent: Wednesday, February 06, 2002 9:55 AM > > > To: [EMAIL PROTECTED] > > > Subject: Re: Sensitivity Analysis > > > > > > On 31 Jan 2002 10:06:36 -0800, [EMAIL PROTECTED] > > > (Christopher J. Mecklin) wrote: > > > > > > > I had a colleague (a biologist) ask me about sensitivity analysis. I am > > > > > not familiar with the technique (above and beyond knowing that the > > > > technique exists). What books/articles/websites/etc. would be good > sources > > > > for my colleague to learn about sensitivity analysis. Since he's a > > > > biologist and not a statistician, I'm assuming he would prefer a > treatment > > > > geared towards application rather than theory. > > > > > > I have not seen any reply to this. I suspect that there might be > > > too many options that refer to 'sensitivity' and none of us > > > are sure what you are interested in, precisely. > > > > > > What's another keyword? I pair specificity with sensitivity; but > > > I don't refer to 'sensitivity analysis', I say 'discriminability.' > > > Your question -- and my background thoughts of 1000-generation, > > > simulation analyses in genetic model ling -- makes me think of > > > something I saw years ago, called 'perturbation analyses'. > > > > > > Try Google, or try us again with additional detail. > > > > > > Hope this helps. > > > -- > > > Rich Ulrich, [EMAIL PROTECTED] > > > http://www.pitt.edu/~wpilib/index.html > > > > > > > > > = > > > Instructions for joining and leaving this list, remarks about the > > > problem of INAPPROPRIATE MESSAGES, and archives are available at > > > http://jse.stat.ncsu.edu/ > > > = > > > > > >= > >Instructions for joining and leaving this list, remarks about the > >problem of INAPPROPRIATE MESSAGES, and archives are available at > > http://jse.stat.ncsu.edu/ > >= > > Christopher J. Mecklin, PhD > Assistant Professor > Department of Mathematics and Statistics > Murray State University > Murray, KY 42071 > Phone: 270 762-5437 > Fax: 270 762-2314 > http://campus.murraystate.edu/academic/faculty/chris.mecklin/index.htm > > > > = > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at > http://jse.stat.ncsu.edu/ > = sensitivity analysis is not the same as sensitivity and specificity from epidemiology. these latter terms are used when describing the characteristics of
panel data - fixed effects
Re: panel data - fixed effects I've been playing with some regressions The sample is 500 listed firms in Malaysia. I'm using MV/BV as a performance measure and various variables such as ownership structure, log of sales etc etc. Someone has suggested I use panel data - fixed effects method Is this referring to pooled data? Do I pool my data over a number of years rather than each individual year? I gather that fixed effects is using dummy variables. What variables might I use as dummy variables? Can you point me in the right direction. I've about a half a dozen books on my desk on stats and econometrics and none give me clear guidance Many thanks Mark = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: 'Distance' between two normal distributions
Francis Dermot Sweeney wrote:
=
> If I have two normal distributions N(m1, s1) and N(m2, =
> s2), what is a good measure of the distance between them? =
> I was thinking of something like a K-S distance like =
> max|phi1-phi2|. I know it probably depende on what I
> want it for, or what exactly I mean by distance, but any =
> ideas would be helpful.
Francis,
This question arises in receiver operating characteristic (ROC)
analysis, where an effective ("latent") pair of univariate normal data
distributions often may be assumed to underlie an ROC curve.
Given two univariate normal probability densities with generally
different means (m1 and m2) and standard deviations (s1 and s2), the
common indices of separation are
d=92_e =3D (m1 - m2)/((s1 + s2)/2)
and
d_a =3D (m1 - m2)/SQRT((s1**2 + s2**2)/2),
whereas a less well-known measure is
Sakitt's D =3D (m1 - m2)/SQRT(s1 * s2).
In the special case where s1 =3D s2 =3D s, all three of these indices red=
uce
to
d' =3D (m1 - m2)/s .
All three indices also apply rigorously to *non-normal*
decision-variable densities in ROC analysis if some (usually unknown)
monotonic transformation of the decision variable yields normal
densities. This generalization is possible because ROC curves are
invariant under any monotonic transformation of the decison axis, so the
requirement for strict interpretability of the indices becomes one of
having an ROC curve that plots as a straight line on "normal deviate
axes" (e.g., see Metz CE. ROC methodology in radiologic imaging. =
Investigative Radiology 1986; 21: 720). In non-normal situations of
this kind, the indices are *not* defined in terms of means and standard
deviations, but instead in terms of the straight-line ROC curve on
normal-deviate axes. If the "y intercept" and "slope" of such an ROC
are given by "a" and "b", respectively, then
d=92_e =3D 2a/(1 + b)
and
d_a =3D a*SQRT(2/(1 + b**2)) ,
whereas
Sakitt's D =3D a/SQRT(b).
All of these indices approach =
d' =3D a
in the special case where b =3D 1. =
When an ROC curve plots as a straight line on normal-deviate axes, its
value of d_a happens to equals the normal deviate which corresponds to
the area under the ROC when that curve is plotted on *conventional*
(i.e., probability, rather than normal-deviate) axes. The latter
interpretation of d_a is sometimes used for other ROC curve forms as
well, which isn't strictly "legal" but, from a practical standpoint, is
rarely misleading.
If you=92d like to do some additional reading, I would recommend that you=
begin with
Simpson AJ, Fitter MJ. What is the best index of detectability? =
Psych Bull 1973; 80:481-488.
And finally, I feel obliged to emphasize the importance of a point that
you raised yourself: The validity of any summary index *does* depend --
sometimes strongly -- upon what it=92s used for.
Hoping this helps,
Charles Metz
=
Instructions for joining and leaving this list, remarks about the
problem of INAPPROPRIATE MESSAGES, and archives are available at
http://jse.stat.ncsu.edu/
=
Re: 'Distance' between two normal distributions
seems, as you have said, depends what you want to do with it if there is considerable overlap, then whatever distance you use will have some of both distributions included ... if there is essentially no overlap ... then any pair of values ... one from each ...will reflect a real difference of course, if there is a small difference in means but very large sds ... that is one thing wheres ... if there were the same small differences in means but, minuscule sds ... that would be another thing the simple thing would be to use the mean difference but, that really does not reflect if there is any overlap between the two and, that seems to be part of the issue At 07:28 PM 2/6/02 +, Francis Dermot Sweeney wrote: >If I have two normal distributions N(m1, s1) and N(m2, s2), what is a >good measure of the distance between them? I was thinking of something >like a K-S distance like max|phi1-phi2|. I know it probably depende on >what I want it for, or what exactly I mean by distance, but any ideas >would be helpful. > >Thanks, >Francis. > >-- > >Francis Sweeney >Dept. of Aero/Astro >Stanford U. > > >= >Instructions for joining and leaving this list, remarks about the >problem of INAPPROPRIATE MESSAGES, and archives are available at > http://jse.stat.ncsu.edu/ >= Dennis Roberts, 208 Cedar Bldg., University Park PA 16802 WWW: http://roberts.ed.psu.edu/users/droberts/drober~1.htm AC 8148632401 = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Slash You Debt Payments! (No Loan Needed) P
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RE: Sensitivity Analysis
Judith, Rich, Art, edstat-l list; My thanks to your replies and my apologies for not articulating my question better in my initial post. To be somewhat less vague about my question (I'll probably be still a little vague because of my lack of knowledge), the colleague of mine who asked about "sensitivity analysis" meant the question in regards to population ecology. To try to be more specific about a topic that I know little about, an ecologist might be modelling the risk of extinction. The model will involve several parameters. The use of the term "sensitivity analysis" in this context apparently means determining how "sensitive" the model's predictions are to uncertainty in the estimates of the parameters to help determine what parameters need to be estimated "more carefully". (These last few sentences were paraphrased from http://www.ramas.com/pva.htm, a hit I got from a hastily conducted Google search of "sensitivity analysis ecological model".) I was sent a list of references by another reader of this newsgroup that I passed on to my colleague that he found satisfactory for his purposes. I suppose I could post that list of references if anyone else is interested. The use of this term "sensitivity analysis" is apparently from the use of the term "sensitivity" in epidemiology (and quite possibly others use of the term). This seems to be one of those situations where the same word means different things to different people. Again, my apologies for the vague request. CJM At 11:27 AM 02/06/2002 -0500, Conn, Judith wrote: >I do know that in epidemiology and medical science the purpose is to find >out how "sensitive" the test is . This ia what I think of when talking >sensitivity analysis. Further info can be obtained from P Armitage & G >Berry, "Statistical Methods in Medical Research", Blackwell Scientific >Publications. Judy Conn > > > -Original Message- > > From: Rich Ulrich [SMTP:[EMAIL PROTECTED]] > > Sent: Wednesday, February 06, 2002 9:55 AM > > To: [EMAIL PROTECTED] > > Subject: Re: Sensitivity Analysis > > > > On 31 Jan 2002 10:06:36 -0800, [EMAIL PROTECTED] > > (Christopher J. Mecklin) wrote: > > > > > I had a colleague (a biologist) ask me about sensitivity analysis. I am > > > > > not familiar with the technique (above and beyond knowing that the > > > technique exists). What books/articles/websites/etc. would be good > > sources > > > for my colleague to learn about sensitivity analysis. Since he's a > > > biologist and not a statistician, I'm assuming he would prefer a > > treatment > > > geared towards application rather than theory. > > > > I have not seen any reply to this. I suspect that there might be > > too many options that refer to 'sensitivity' and none of us > > are sure what you are interested in, precisely. > > > > What's another keyword? I pair specificity with sensitivity; but > > I don't refer to 'sensitivity analysis', I say 'discriminability.' > > Your question -- and my background thoughts of 1000-generation, > > simulation analyses in genetic model ling -- makes me think of > > something I saw years ago, called 'perturbation analyses'. > > > > Try Google, or try us again with additional detail. > > > > Hope this helps. > > -- > > Rich Ulrich, [EMAIL PROTECTED] > > http://www.pitt.edu/~wpilib/index.html > > > > > > = > > Instructions for joining and leaving this list, remarks about the > > problem of INAPPROPRIATE MESSAGES, and archives are available at > > http://jse.stat.ncsu.edu/ > > = > > >= >Instructions for joining and leaving this list, remarks about the >problem of INAPPROPRIATE MESSAGES, and archives are available at > http://jse.stat.ncsu.edu/ >= Christopher J. Mecklin, PhD Assistant Professor Department of Mathematics and Statistics Murray State University Murray, KY 42071 Phone: 270 762-5437 Fax: 270 762-2314 http://campus.murraystate.edu/academic/faculty/chris.mecklin/index.htm = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
EViews 3.1 error message
Hi, I tried to run a workfile on EViews 3.1 that I had created in EViews 4.0. It is a three equation system estimated via full information maximum likelihood. It worked fine in 4.0. Now, I'm using 3.1 and it opens the 4.0 workfile no problem but when I hit the estimate button (via FIML) it returns: error, near singular matrix. As far as I know the workfile was unchanged from the one that worked fine in 4.0. Do I need to create a new workfile in 3.1 and re-enter the equations and re-import the excel file to make it work in 3.1? thanks, james = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
'Distance' between two normal distributions
If I have two normal distributions N(m1, s1) and N(m2, s2), what is a good measure of the distance between them? I was thinking of something like a K-S distance like max|phi1-phi2|. I know it probably depende on what I want it for, or what exactly I mean by distance, but any ideas would be helpful. Thanks, Francis. -- Francis Sweeney Dept. of Aero/Astro Stanford U. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: can multicollinearity force a correlation?
I can't help it. the last paragraph in this post absolutely _demands_ a response. Wuzzy wrote: > > You made a model with the "exact same exposure in different units", > > which is something that no one would do, > > Hehe, translation is don't post messages until you've thought them > through. > > Anyway, turns out that the answer to my question is "No".. > Multicollinearity cannot force a correlation. It turns out that ONE > of the variables *was* correlated With R^2=0.45 and so > multicollinearity had no effect on overall R^2. > > I'm sure no-one is interested in my data as it has nothing to do with > statistics, my subject of interest is not statistics.. but i need to > learn it as a tool.. Dear Wuzzy, In two short sentences, you have expressed the fundamental issues of those who claim their "subject is not statistics." So long as you try to separate 'statistics' from your specific technology, you will not develop much of either. House builders do not spend much time concerned with their hammers or their nails. Yet they are sufficiently concerned that (in the USA) they buy expensive nail guns and special nail packages so they can build those houses faster and better. They use roofing nails to hold the roof shingles in place, finishing nails to hold the interior trim in place, and they carefully know the differences between them. In resolving a technical product performance problem, which is what I largely do with my statistics, I have to carefully decide what I am going to measure, how it will be measured, and how I will analyze it (crunch the numbers). Many people believe that this last step equals statistics. They neglect that the analysis methods depend on those first two items. They often neglect that each of those numbers I crunch _means_ something. They have units. They relate back to what was measured. The statistical analysis in my view is mostly concerned with detecting and quantifying the relationships between the different things and conditions which were measured. Thus, without the statistics, you have no technology; without the technology you have no statistics. You cannot relegate one of them down to the level of 'tool.' Down that path lies the perennial question, 'which equation should I use,' which begs its own questions. In your specific case, it appears that you tried to do a multiple regression using one response (dependent variable) and three factors (independent variables). But the three factors were actually transformations of the same variable. Since you said they were in different units, the transformations were probably linear. If you tried to do a full multiple regression on this data in this manner (3 factors), I'm surprised that the software did not warn you it had found a singular matrix, or at least that it had tried to divide by zero. Perhaps you made the conversions on a hand calculator, so small rounding errors kept the matrix that is inside the analysis from blowing up (inward!?:) on you. In any case, discovering that a linear transformation of data produces radically different r^2 values should be a warning that something is amiss, and it is time to think more carefully about exactly what digits are being pushed around the screen. Those numbers _mean_ something, remember :) And so does the math of the equations we select. A correlation and/or linear or polynomial regression analysis with one response and one factor would probably be more technically valuable, for your data, as best I can see from here. As for interest in your data, I can say that I would like to see it, as an example I can use for students. I need to collect real data from many different technologies - industrial, business, medical, social sciences, etc. - in order to relate the topic of 'statistics' to the areas of interest to them. I will be happy to share the write up with you, especially if you are willing to correct any errors in the technology which I am likely to make. I am also careful not to slam even the fictitious people who appear in them. After all, it takes an expert to make a good hammer, and an expert to make a good house. They need each other, just as 'statisticians' need 'technology experts.' Cheers, Jay -- Jay Warner Principal Scientist Warner Consulting, Inc. North Green Bay Road Racine, WI 53404-1216 USA Ph: (262) 634-9100 FAX: (262) 681-1133 email: [EMAIL PROTECTED] web: http://www.a2q.com The A2Q Method (tm) -- What do you want to improve today? = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Well I'll be damn!!!!
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RE: Sensitivity Analysis
I do know that in epidemiology and medical science the purpose is to find out how "sensitive" the test is . This ia what I think of when talking sensitivity analysis. Further info can be obtained from P Armitage & G Berry, "Statistical Methods in Medical Research", Blackwell Scientific Publications. Judy Conn > -Original Message- > From: Rich Ulrich [SMTP:[EMAIL PROTECTED]] > Sent: Wednesday, February 06, 2002 9:55 AM > To: [EMAIL PROTECTED] > Subject: Re: Sensitivity Analysis > > On 31 Jan 2002 10:06:36 -0800, [EMAIL PROTECTED] > (Christopher J. Mecklin) wrote: > > > I had a colleague (a biologist) ask me about sensitivity analysis. I am > > > not familiar with the technique (above and beyond knowing that the > > technique exists). What books/articles/websites/etc. would be good > sources > > for my colleague to learn about sensitivity analysis. Since he's a > > biologist and not a statistician, I'm assuming he would prefer a > treatment > > geared towards application rather than theory. > > I have not seen any reply to this. I suspect that there might be > too many options that refer to 'sensitivity' and none of us > are sure what you are interested in, precisely. > > What's another keyword? I pair specificity with sensitivity; but > I don't refer to 'sensitivity analysis', I say 'discriminability.' > Your question -- and my background thoughts of 1000-generation, > simulation analyses in genetic model ling -- makes me think of > something I saw years ago, called 'perturbation analyses'. > > Try Google, or try us again with additional detail. > > Hope this helps. > -- > Rich Ulrich, [EMAIL PROTECTED] > http://www.pitt.edu/~wpilib/index.html > > > = > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at > http://jse.stat.ncsu.edu/ > = = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: Sensitivity Analysis
On 31 Jan 2002 10:06:36 -0800, [EMAIL PROTECTED] (Christopher J. Mecklin) wrote: > I had a colleague (a biologist) ask me about sensitivity analysis. I am > not familiar with the technique (above and beyond knowing that the > technique exists). What books/articles/websites/etc. would be good sources > for my colleague to learn about sensitivity analysis. Since he's a > biologist and not a statistician, I'm assuming he would prefer a treatment > geared towards application rather than theory. I have not seen any reply to this. I suspect that there might be too many options that refer to 'sensitivity' and none of us are sure what you are interested in, precisely. What's another keyword? I pair specificity with sensitivity; but I don't refer to 'sensitivity analysis', I say 'discriminability.' Your question -- and my background thoughts of 1000-generation, simulation analyses in genetic model ling -- makes me think of something I saw years ago, called 'perturbation analyses'. Try Google, or try us again with additional detail. Hope this helps. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
WSCH : A Revolutionary Acne Treatment and More RHOKEN
Title: SPECIAL ALERT Special Alert : WASATCH PHARMACEUTICALS (OTCBB: WSCH)TOP 4 REASONS TO BUY WSCH1.The products and medical therapies developed by WSCH represent possibly the most important breakthrough in the field of Dermatology in the last fifty years.2.WSCH anticipates FDA approval on seven over-the-counter products within the next year, which will provide significant revenue in the retail drug market.3.WSCH has experienced a success rate of 90% during clinical studies, completely eliminating skin disease from 90% of all patients treated.4.By year five, WSCH plans to have annualized revenue over $525 million and over $125 million in EBIT. This does not take into account income from OTC products which will be substantial. PROJECTIONS, OBJECTIVES AND STATISTICS Over a five year period, AISC (WSCH's subsidiary) plans to establish 350 clinics in over 100 major population areas. The company plans to hire over 150 medical doctors for these clinics, train over 1,000 medical assistants and treat over 2,000,000 patients. Also by year five, WSCH plans to have annualized over $525 million in revenue and over $125 million in EBIT. This does not take into account income from OTC products which will be substantial.As of 1991, there were approximately 14 million chronic acne and eczema patients annually in the United States, with the highest percentage between 18 to 44 years of age. The actual number of patients with any type of acne Is significantly higher. Seven billion dollars is spent annually on dermatological pharmaceutical products for these disorders.In 1994, the teen population reached 25 million. During the next decade, it will grow at nearly twice the rate of the overall population (according to U.S. Census Bureau projections). Acne patients are primarily teenagers, whereas eczema patients range from infants to the elderly. SYMBOL: WSCH CURRENT PRICE: $0.059 52 WEEK HIGH: $27.50 52 WEEK LOW: $0.056COMPANY BACKGROUNDWasatch Pharmaceutical, Inc. is a fourteen year old company with a record of outstanding achievements in the field of Dermatology. Dermatology. Under the name of its subsidiary, American Institute of Skin Care (AISC), Wasatch has operated two prototype clinics for the last five years where the products and medical therapies have been tested and proven on hundreds of patients. The Company's activities have been centered on research in the area of serious skin diseases. A concurrent discovery and benefit is WSCH's dramatic success in the area of skin rejuvenation.Seeing the high growth potential from major funding, WSCH elected to become a public company less than two years ago.Wasatch's major successes in the area of skin diseases include:Cystic Acne, Eczema, Seborrhea, Contact Dermatitis, Molluscum, Folliculitis, Acne Rosacea and less prevalent skin diseases.Interestingly, these skin disorders account for more than 70% of all business in the field of dermatology for which there are very few (if any) safe, effective therapies like those developed by Wasatch.Because the therapies developed by Wasatch dominate this area of medicine, WSCH has elected to market its products via company-owned clinics throughout the United States. This decision has resulted in the establishment of two research clinics in Utah for the purpose of implementing procedures within the clinics pursuant to testing and confirming the results that were achieved in past clinical trials. Due to its success rate of 90% on hundreds of patients over a five year period, WSCH's clinics are now on line with insurance providers independent of HMOs. Efforts to establish Preferred Providership status with HMOs are presently being pursued.THIS JUST IN : WSCH BREAKING NEWS Wasatch Pharmaceutical Inc. Announces a New Physician Marketing Campaign and Listing On German Stock Exchanges MURRAY, Utah--(BUSINESS WIRE)--Nov. 27, 2001--Wasatch Pharmaceutical Inc. (OTCBB:WSCH - news) CEO Gary Heesch announced today a marketing campaign directed to physicians. A direct link has been established on a physician recruiting Web site making available therapies for the treatment of cystic acne, acne, folliculitis and skin rejuvenation. Physicians will find the benefits of these treatment therapies by logging on to the "X Acne" link at the Physician Search website. This physician search Web site typically receives over 200,000 hits per month. Mr. Heesch reminded, "Our treatment therapy products are also available via the AISC Online Store."These skin treatment products come in kit form providing a 90-day supply to patients for the full treatment program. Included in the kit is an instructional video on the treatment therapy allowing the patient to use these products in their home. The therapies, when used as instructed, achieve a success rate of eradication in excess of 90% with no side effects of any consequence. Previousl
Hello!
I'm russian student/ Alex Seregin/ = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: can multicollinearity force a correlation?
Dear Wuzzy The answer is yes they can. Consider the case where x1 is highly correlated to x2 and Y is correlated with X1-X2. I on a simulation of this for 100 cases got a R-squared for the regression model of .998 but the individual correlations x1 vs y = -.072 p=.476 x2 vs y=-.105 p=.301 x1 vs x2=.999 p<.001 This was a simulation and this situation is a minority case in my experience but the answer is yes they can. However this case is of course a nonsense if you have perfectly correlated cases as you would have if only the units had been changed. Jean M. Russell To: [EMAIL PROTECTED] Date sent: 5 Feb 2002 18:15:00 -0800 From: [EMAIL PROTECTED] (Wuzzy) Organization: http://groups.google.com/ Subject:Re: can multicollinearity force a correlation? > In my own defense: > > I was asking a simple question: > > will highly correlated cause an irregularly high R^2. > > My answer to my own question is "no" it can't.. > No-one here was able to give me this answer and I believe it is > correct: if your sample is large enough,(as mine is) then "no", > multicollinearity cannot affect your R^2, it will only affect the > coefficients and their signs and errors. > > > = > Instructions for joining and leaving this list, remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are available at > http://jse.stat.ncsu.edu/ > = -- Jean M. Russell M.A. M.Sc. [EMAIL PROTECTED] Corporate Information & Computing Services, University of Sheffield 285 Glossop Road Sheffield S10 2HB United Kingdom Phone: 0114-222-3098 Fax : 0114-222-3040 = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
toner cartridges
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