Likewise, the coefficient of salary is the slope of the baseline company, and the coefficient of salary_d is the deviation of the comparison group's slope from the baseline slope. [Thread Prev][Thread Next][Thread Index] st: FW: comparing coefficients between 2 models with suest and pweight. qui xtlogit Iy x1 x2 if q==5,i(isub) nolog . I know that - suest - does not work with xtreg, so I considered the "demean your data by hand" method as suggested by Prof. Schaffer in the old forum. Note, however, that the formula described, (a-c)/(sqrt(SEa^2 + SEc^2)), is a z-test that is appropriate for comparing equality of linear regression coefficients across independent samples, and it assumes both models are specified the same way (i.e., same IVs and DV). That all works well,i.e., the estimated coefficients from the regress models are the same as with the xtreg, fe command. Suest stands for seemingly unrelated estimation and enables a researcher to establish whether the coefficients from two or more models are the same or not. . Sometimes your research may predict that the size of a regression coefficient should be bigger for one group than for another. I want to test if $\beta$ and $\omega$ are statistically different. Because there were some missing values for the variable rep78, Stata used only 69 (rather than the full 74) pairwise observations. Login or Register. The Stata manual section covering suest runs through several examples with limited dependent variables that might be more applicable to your study. I have seen a guide to do that using Stata suest but only applies to one independent variable model. I wonder if that is possible to compare coefficients between two multivariate regression model? Cite. I actually don't know if this is totally legitimate but it seems to work (I know, hardly the reassurance you are looking for, but I believe this is okay and would happily stand corrected if it isn't). The suest statements performs seeming unrelated regression on both group1 and group2 with clustered standard errors and then tests the equality of coefficients. > hi all, > > I'm interested in compare two coefficients from the following two > regressions: > y=a0+a1*X1+a2*X2+ey > z=b0+b1*X1+b2*X3+ez > Under the idea case of OLS regression, I can use SURE regression to achieve > efficiency and easily test whether a1=b1. Number of obs: This is the number of pairwise observations used to calculate the Spearman Correlation Coefficient. From Thorhildur Olafsdottir To "statalist@hsphsun2.harvard.edu" … Various selection criteria, such as semipartial correlations, are discussed for model selection. Spearman’s rho: This is the Spearman correlation coefficient. My first thought would be to use something along the lines of sureg or suest combined with lincom, but I can't quite figure out a way to make it work. sureg and suest do not work with ivregress(as far as I'm concerned), and with lincom I can't find a way to access the coefficients and their standard errors. On Statalist you suggest the following: "What I meant is that I can think of two main uses for -suest-. Now, conduct the Chow Test using the .test command. est store q5 . If the coefficients themselves (rather than the variables) have an asymptotic normal distribution then you should be able to use t-tests. I am trying to compare the coefficients of two panel data regressions with the same dependent variable. Log in with; Forums ; FAQ; Search in titles only. The fourth edition of the book has been updated to include new features in Stata 13. qui xtlogit Iy x1 x2 if q==6,i(isub) nolog . Acock also covers a variety of commands available for evaluating reliability and validity of measurements. If the models were multinomial logistic regressions, you could compare two or more groups using a post estimation command called suest in stata. Here is a simple way to test that the coefficients on the dummy variable and the interaction term are jointly zero. I found that 'suest ' of Stata is a very useful command for comparing regression coefficients between different (separated) regression models EASILY. I have seen a guide to do that using Stata suest but only applies to one independent variable model. Home; Forums; Forums for Discussing Stata; General; You are not logged in. Comparing Logit & Probit Coefficients…Richard Williams, ASA 2012 Page 5 In Stata, heterogeneous choice models can be estimated via the user-written routine oglm. Methodology and Stata Journal) shows promise According to KHB, their method separates changes in coefficients due to rescaling from true changes in coefficients that result from adding more variables to the model (and does a better job of doing so than y-standardization and other alternatives) Dear all, I have estimated a fixed effect panel regression model for two groups in my data set. I am trying to use Suest to compare the coefficients of a regressor in two regressions ran on two different datasets. This is, in effect, testing if the estimated parameters from the first regression are statistically different from the estimated parameters from the second regression: If you concluded that they are not equal, then it is obvious from inspection that sranklow is the bigger of the two. est store q6 . (Also, note that if you use non-linear transformations or link functions (e.g., as in logistic, poisson, tobit, etc. Comparing fixed effects coefficients between two groups 14 Apr 2017, 14:20. We can compare the regression coefficients among these three age groups to test the null hypothesis. Race is of course nominal, and income and age are binned as well, but I treat the income bins as a linear effect. Below, we have a data file with 10 fictional females and 10 fictional males, along with their height in inches and their weight in pounds. Researchers often want to assess the effect of a particular variable on some dependent variable net of one or more confounding variables. Test equality between coefficients in STATA. Comparing coefficients across logit and probit models In linear regression, the concept of controlling for possible confounding variables is well understood and has great practical value. Notice that the constant and the coefficient on x are exactly the same as in the first regression. We can formally test that coefficients are the same for the full model m1 and the restricted models m2 and m3 by using the hausman command. What I am aiming at is the following: y1 = c + β x y2 = c + β x In Stata . Search in General only Advanced Search Search. Stata: Data Analysis and Statistical Software . The fear of crime variables are coded as Likert items with a scale of 1-5, (higher values are more safe) but I predict them using linear regression (see the Stata code at the end though for combining ordinal logistic equations using suest). * oglm replication of Allison’s Table 2, Model 2 with interaction added: However, it is also useful in situations that involve simple models. März 2010 21:40 To: [hidden email] Subject: st: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering Dear Statalist, I use "estimates store + suest + test" to compare regression coefficients between two samples. Comparing the coefficients between models does not suggest substantial differences. Solution 2: Try suest. It seems that 'suest' command does not work with 'xtreg'. The most important, it … Prompted by a question on Statalist relating to efforts to compare (with a TTest) whether coefficients in two separate regression models systematically differ I stumbled upon the suest command.With the suest command, one can, e.g., regress one model, store its results, regress a second model, store its results, and then compare them with the test command. You can browse but not post. See article by Mize et al (2019) in Sociological Methodology. Ask Question Asked 2 years, 1 month ago. 2. between the quantiles (using sqreg). I am trying to test whether the coefficients are significantly different between groups, but suest does not seem to be compatible with the mixed command. Re: Comparing coefficient across two xtmixed (growth curve) models Hi Lance, You could try a (pseudo-) multivariate model. xtreg y1 x i.z xtreg y2 x i.z I want to check whether the βs are significantly different. And I want to test if the coefficients are significantly different for both group. Also, you can compare marginal effects. Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org. I wonder if that is possible to compare coefficients between two multivariate regression model? stata gsem standardized coefficients, of effect sizes and standardized coefficients. Related to Sharon's question, I have a similar problem, where I want to estimate the covariance between estimated regression coefficients obtained under clustering, but for two different indicator variables with the same predictors: . I estimate them using the STATA command reg2hdfe with cluster at individual level. For example, you might believe that the regression coefficient of height predicting weight would be higher for men than for women. Dear Stata Forum, I was trying to compare (or test the equality of) the coefficients 1. of the same specification (using 'xtreg') but for male and female samples using 'estimates store' and then 'suest' command. It's the block of code from suest down that I cannot figure out in SAS. gsem is a very flexible command that allows us to fit very sophisticated models. I have understood that suest does not work with reghdfe. does men and woman have the same betas). Ho: B 1 = B 2 = B 3. where B 1 is the regression for the young, B 2 is the regression for the middle aged, and B 3 is the regression for senior citizens. I would normally use suest but it is not possible with reg2hdfe. One is comparing the same model with different samples (e.g. For example, when we want to compare parameters among two or more models, we usually use suest, which combines the estimation results under one parameter vector and creates a simultaneous covariance matrix of the robust type. In Stata you can use suest and test to do it. Is there any other way to compare between male and female parameters? Statistical methods are developed for comparing regression coefficients between models in the setting where one of the models is nested in the other. > > Unfortunately, y is truncated in my data and z is a dummy and thus a probit > will > be a better choice. The first two regress statements perform OLS and save the coefficients, which I know how to do in SAS. 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