regression model

  1. K

    Measuring the effect of in-store Promotions

    Hello, I am testing the effect of a new in-store promotion technique (treatment). It is applied during product promotions, as a compliment to regular promo displays, to further improve sales. I have the treatment in only one store but on several products promotions in that store (I have...
  2. L

    Finding my control group PSM, Matching or regression model and correct for confounder

    Hey there, First off I'm hoping I'm posting this in the right place. I'm doing research where there is a patient group of n=9 that underwent our new treatment. Whilst there is a group of n=140 that underwent the regular treatment. Now my prof. wants me to find the 18 most matching...
  3. J

    Dealing with missing values

    I am analyzing the data of a cohort study.There are three sets of paired data (same measures on same subjects in 3 different point of time). The problem is that the third set of data have more than 50% missing values. my question is that, how can i deal with these missing? does MI help in these...
  4. rogojel

    Model vs. test

    Hi, we just had an interesting discussion about the chi-squared test, that could be generalized. I think the core of the discussion was whether one should prefer a simple statistical test or a statistical model - e.g. a chi-squared test vs. a logistic regression. Given that in practice one is...
  5. V

    Change regression model ($x^*_i = x_i -10$)

    Hi there.:wave: I'm solving an exercise on multiple linear regression. Near the end I will be asked for the same data as the previous model, it is the maximum likelihood estimates. The previous model: I have the matrix (X'X)^{-1} and the matrix X'y and the model is: Y_i = B_0...
  6. Y

    Regression with different lengths of data series

    Dear All, I am trying to do a multivariate regression, i.e. y = ax1+bx2. but x1 has data from year 1 to year 30, but x2 has only year 20 to year 30. How can I fit such a model to the different lengths of time series? Thanks a log, Yiwu
  7. J

    How do I test the significance of my correlation coefficients for various regressions

    Hi, I have a set of 25 points and I used a TI-84 calculator to calculate the linear, quadratic, logistic, exponential, and power regression models for this data set. I have, likewise, obtained the r^2 value for each of these regressions. Some of these r^2 values appear to be quite similar. For...
  8. R

    How to handle missing values in lm.fit?

    Is there a way to use lm.fit without completely removing rows with missing data using R? Is there a way for lm.fit to leave out one piece of missing data but compare the rest? I've tried all of the na.actions and can't seem to find one that works. Any help is appreciated. Thanks!
  9. P

    PAF through formula or through Conditional Logistic Regression

    Hi all, In a large registry dataset of psychiatric patients, if one wants to find the excess risk of schizophrenia patients developing depression, what would be the best method to apply: 1) Use the relevant formula to calculate PAF (Population Attributable Fraction). Formula can be...
  10. P

    linear regression - modelling dependent variables

    I'm trying to estimate the value of an apartment, by doing a regression through similar apartments. The regression model looks now like this lmRob(price ~ ., data = data) , but this is clearly wrong. My problem is modelling variables which are depending on each other. For example floor...
  11. S

    proving regression with dummy variables gives same estimates as separate models

    See attachment for problem description: To prove this I started by using: vector of Beta estimates for category k = [Bk], matrix of estimates for category k = [Xk], Y estimates for category = [Yk]. 1. Find betas for single category: Calculating [Ba] = (Xa' * Xa)inv * (Xa' *Ya) for the 2. Find...
  12. Y

    What type of curve is this?

    The left one is a logistic curve / sigmoid function e.g. y=1 / 1+exp(-bx) What would be the typical name for the curve on the right / typical functional form? :confused:
  13. F

    Dependent variable in regression model - sum of factors?

    I got across below article due to one of our student used it for the brand loyalty measure. http://www.palgrave-journals.com/jt/journal/v15/n4/full/5750044a.html I have a hard time to understand what is the dependent variable in this regression model - I did not find it explicitly mentioned...
  14. A

    Outliers

    Hello there, I have data set of 5846 observations out of which 15 observations are outliers. I need to perform multiple linear regression which as I know is highly sensitive to outliers. Do I have to filter those 15 outliers out or they will not mess up my analysis, since the number of...
  15. Z

    How do I interpret regression coefficients when there are log transformations?

    Hi, I'd like to know how to interpret with percentage the slope coefficients of a regressoin when I have: A- log(Y) ~ log(X) b- log(Y) ~ X c- Y ~ log(X) So far I found this web site, but I'm not sure it is accurate: http://www.ats.ucla.edu/stat/sas/faq/sas_interpret_log.htm...
  16. Z

    Regression fitted values

    I'm working with a dataset that I'm using to model total biomass (which was a variable created by adding three components of biomass). I also modeled each of these components as a function of the same variable. I am comparing the predicted value of the total biomass model with the sum of the...
  17. H

    Gaussian Processes - Wiener process - The drunk particle

    Hello, I recently read about Gaussian Processes (http://en.wikipedia.org/wiki/Gaussian_process) for non linear regression. I am not an expert but I found it quite interesting how to see for example a wiener process from the Gaussian processes perspective. An interesting example came to my...
  18. D

    Interval independent variable in binary logistic regression

    Hi everyone: I am a bit new to logistic regression and I could use some advice. I am trying to discover the influence of various variables on voting turnout in an election study. Although I have one problem: The household income variable is coded as interval variable with 16 categories, each...
  19. D

    Did I deisgn this wrong? Using dummy variables for Y

    Hi all, Thanks for taking a look at this. Regression Statistics Multiple R 0.908734206 R Square 0.825797856 Adjusted R Square 0.824730441 Standard Error 0.111438927 Observations 822 I'm looking at a group of employees that either resigned or remained active with our...
  20. A

    Liner regression interpretation

    Hello Seniors, In my regression analysis I want to find, how “% change” is affected by other variables, the day of the month (Sunday, Monday etc.) and the occurrence number of that that day in that particular month (first occurrence of Sunday=1, second occurrence=2 so on and so forth for...