# Search Results

Results tagged with Search options user 5191
11 results

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

Starting from your first approach: If you treat the data as if it had only 7 observations, you need to weight them with the size of the group. Refer to this question for how to do regression with …
answered Jan 31 '14 by mzuba
You would probably want to test the hypothesis that the outcome is different in these two groups. Since the scale of the dependent variable is ordinal, you want to perform a Wilcoxon-Mann Whitney U- …
are around 6–8. OLS regression seems to be a poor choice to me, as it might produce predicted values outside the 1–10 interval. My colleagues have suggested that I might take a look at truncated … /censored analysis, such as tobit regression. However, I do not believe that I have data which is censored in the way tobit regression would assume, which would be the case if only part of the real …
asked May 3 '12 by mzuba
Multinomial logistic regression works like a series of logistic regressions, each one comparing two levels of your dependant variable. Here, category 1 is the reference category. For example … , consider the case where you only have values where category is 1 or 5. (Recode that to 0 and 1, so that you can perform logistic regression.) The coefficients of line 5 of your output represent the variable coefficients such a logistic regression would yield. …
answered Dec 3 '12 by mzuba
Insignificant at the 10% level means that the 90%-confidence interval overlaps with zero. A significant difference at the 1% level means that the (larger!) 99% confidence intervals do not overlap. Thi …
answered Mar 26 '12 by mzuba
others that I might include in later stages). Suppose my regression model is $y_t = β_0 + β_1 age + β_2 sex + β_3y_{t-1} +u$. Since R provides me with coefficients for the betas, it is easy to …