Rich Ulrich wrote: > On 12 Mar 2004 09:00:42 -0800, [EMAIL PROTECTED] wrote: > > >>I really need a hand with a regression analysis for my thesis. >>I'll try as best I can to summarize/explain. I have a DV, time on >>task. I have a number of IVs, demographics of the participant, >>cognitive tests. >> >>Generated a series of bivariate correlations for time on task. >>Took all significant correlates of Time On Task (11 variables) and >>entered them in a hierarchical regression, the ordering based on the >>strength of the correlation. > > > Well, that's a bad idea right there. You can see my stats-FAQ for > comments about stepwise regression, and further references. > How many variables did you *start* with? - Since there > were a lot, your procedure puts you into an exploratory mode > where testing has been fatally undermined; > and the "stepping" is mainly useful for selecting > a *concise* model with few variables, assuming that you > are confident that they really matter, and cover what else > matters. > > Rich, I tend to agree with you about the potential abuse of stepwise multiple regression. However, it is widely used and I wouldn't label a study using stepwise as being of necessity flawed, even if the goal was to evaluate the relative importance of different explanatory variables. For example, this week's Science has an article that has been widely reported in the popular press and the key analysis is a stepwise regression. One way of interpreting the paper is that the authors used stepwise to make their assessment of the importance of N deposition more objective. They didn't pick N deposition, the computer did.
Stevens, Carly J., Dise, Nancy B., Mountford, J. Owen, Gowing, David J. Impact of Nitrogen Deposition on the Species Richness of Grasslands Science 2004 303: 1876-1879 http://www.sciencemag.org/cgi/content/full/303/5665/1876 From the paper: For each site, we compiled a data set of the potential drivers on plant species richness, including all of those described as globally important (15): nine chemical environmental factors [deposition of reduced inorganic N (NH3, NH4+), oxidized inorganic N (NO, NO2, NO3�), and total inorganic N; deposition of SO42�; acid deposition (total inorganic N + SO42�); topsoil (A or O horizon) pH and subsoil (30 to 40 cm) pH; topsoil percentage of N; and topsoil C:N ratio]; nine physical environmental factors (mean annual temperature and precipitation, actual and potential evapotranspiration, soil moisture deficit, litter cover, altitude, slope, and aspect); and two human modifications (grazing intensity and enclosures) (table S1). These variables were entered into a stepwise multiple regression with site species richness as the dependent variable. ... Of 20 variables measured to account for the variability in species richness, total deposition of inorganic N (Ndep, kg N ha�1 y�1) was the most important predictor, explaining more than half of the variation in the number of species per quadrat (Fig. 2A and Eq. 1). ... After accounting for N deposition, mean annual precipitation (MAP, mm) explained an additional 8% of variability in species richness. A further 5% was explained by the A horizon soil pH (Top pH, Fig. 2B) and 3% by altitude (Alt, m). In total, 70% of the variability in species richness could be explained by these four variables: ... . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
