Recent content by GretaGarbo

  1. GretaGarbo

    Trend analysis

    No trend!
  2. GretaGarbo

    Trend analysis

    Can you plot the curve? delay vs time point.
  3. GretaGarbo

    Which statistical test to use

    What is the model?
  4. GretaGarbo

    testing the association between points and any of the points belonging to another set of point: am I approaching it correctly?

    Yes, I think you are right. If you have an area where there is uniform density for an event (like a point on the x,y coordinate) and you have a small part of that area, irregular polygon or not, then the probability for say k events in the polygon will be binomial distributed out of n events...
  5. GretaGarbo

    Standardizing Performance (sports-related)

    You could search for "Elo rating" that has been used in chess but also in football. You can see how to convert an Elo rating difference to probability to win for teams with rating like 1500 or 2000. You will need to go back a few seasons to give every team an Elo rating. The model is essentially...
  6. GretaGarbo

    making R computing large factorials

    Yes.
  7. GretaGarbo

    making R computing large factorials

    Remember that as "n" gets large so that n*p is large, the binomial is approximated by the normal distribution. The rule of thumb used to be n*p>5. So if p is "in the middle" (0.2<p<0.8) and n is larger than 10, it is well approximated by the normal. (Of course mu=n*p and variance =n*p*(1-p).)...
  8. GretaGarbo

    making R computing large factorials

    (Sorry, I had not been reading so carefully.) You have n points, x of them falls into your polygon so that you have 0, 1, 2, 3 to x within polygon. x successes out of n. I should say that I have not read carefully and I have not understood what you are really aiming to. (Just trying to...
  9. GretaGarbo

    making R computing large factorials

    I believe that you need dbinom(). ("d" for density.) pbinom gives you the cumulative distribution function. # dbinom(x, size, prob, log = FALSE) dbinom(2, size=4, prob= 0.5) #[1] 0.375 dbinom(0:4, size=4, prob= 0.5) # [1] 0.0625 0.2500 0.3750 0.2500 0.0625 x is the number "heads" and size...
  10. GretaGarbo

    Estimate sample size needed for valid study of medical test

    Rune! What do you mean by this? Do you have a single variable e.g. a blood sample and for high/low values you would get high risk or low risk? Then I come to think of roc-curves, receiver operating characteristic. If you want to combine many variables to classify to high/low risk other...
  11. GretaGarbo

    Linear Probability Model

    The thing with generalized linear models is that you can choose your self what kind of link function you want. Just like you can choose to include or not to include an x-variable. So the link can be the logit link function or the identity link function (like in LPM) or the probit link of the...
  12. GretaGarbo

    Help with ANOVA

    That was absolutely not my intention. I apologize. But you are not the first one using the three-number. I just wonder where people get things from. So, OK there you go. You have a pilot plant estimate. And it is not to little data. (And I do not intend to be "condescending" now either.) I...
  13. GretaGarbo

    Help with ANOVA

    Can you tell us where the number of three comes from? It it not a holy number is it? (Joseph, Maria and Jesus). I believe that they don't want to do just one. They want to replicate. But with two there could be one outlier. So they recommend Three, because then they can compare the two with the...
  14. GretaGarbo

    Need help to decide which statistical test to use

    I would guess that this is not a balanced design (They have hardly randomized people to different treatments) so I guess that the full factorial can not be estimated. But I guess that the main effects can be estimated.
  15. GretaGarbo

    Need help to decide which statistical test to use

    There seems to be four factors (knee replacement and Hip, race groups, insurance types, different age groups) where age could be a covariate = a regression variable.