The first two regress statements perform OLS and save the coefficients, which I know how to do in SAS. It's the block of code from suest down that I cannot figure out in SAS. If the coefficients themselves (rather than the variables) have an asymptotic normal distribution then you should be able to use t-tests. 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). Re: Comparing coefficient across two xtmixed (growth curve) models Hi Lance, You could try a (pseudo-) multivariate model. Test equality between coefficients in STATA. I want to test if $\beta$ and $\omega$ are statistically different. 2. between the quantiles (using sqreg). Number of obs: This is the number of pairwise observations used to calculate the Spearman Correlation Coefficient. Login or Register. I am trying to compare the coefficients of two panel data regressions with the same dependent variable. The most important, it … In Stata you can use suest and test to do it. If you concluded that they are not equal, then it is obvious from inspection that sranklow is the bigger of the two. Now, conduct the Chow Test using the .test command. 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. > 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. 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). Notice that the constant and the coefficient on x are exactly the same as in the first regression. However, it is also useful in situations that involve simple models. Comparing the coefficients between models does not suggest substantial differences. I wonder if that is possible to compare coefficients between two multivariate regression model? does men and woman have the same betas). Spearman’s rho: This is the Spearman correlation coefficient. And I want to test if the coefficients are significantly different for both group. One is comparing the same model with different samples (e.g. I am trying to use Suest to compare the coefficients of a regressor in two regressions ran on two different datasets. Various selection criteria, such as semipartial correlations, are discussed for model selection. Is there any other way to compare between male and female parameters? Solution 2: Try suest. Home; Forums; Forums for Discussing Stata; General; You are not logged in. We can compare the regression coefficients among these three age groups to test the null hypothesis. 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. Also, you can compare marginal effects. Because there were some missing values for the variable rep78, Stata used only 69 (rather than the full 74) pairwise observations. 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. Search in General only Advanced Search Search. 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) (Also, note that if you use non-linear transformations or link functions (e.g., as in logistic, poisson, tobit, etc. 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. I found that 'suest ' of Stata is a very useful command for comparing regression coefficients between different (separated) regression models EASILY. qui xtlogit Iy x1 x2 if q==5,i(isub) nolog . 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: . 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. 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. On Statalist you suggest the following: "What I meant is that I can think of two main uses for -suest-. 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. Here is a simple way to test that the coefficients on the dummy variable and the interaction term are jointly zero. I estimate them using the STATA command reg2hdfe with cluster at individual level. xtreg y1 x i.z xtreg y2 x i.z I want to check whether the βs are significantly different. 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). I wonder if that is possible to compare coefficients between two multivariate regression model? 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. est store q6 . If the models were multinomial logistic regressions, you could compare two or more groups using a post estimation command called suest in stata. gsem is a very flexible command that allows us to fit very sophisticated models. 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. Comparing fixed effects coefficients between two groups 14 Apr 2017, 14:20. Stata: Data Analysis and Statistical Software . It seems that 'suest' command does not work with 'xtreg'. Cite. Race is of course nominal, and income and age are binned as well, but I treat the income bins as a linear effect. * oglm replication of Allison’s Table 2, Model 2 with interaction added: This is, in effect, testing if the estimated parameters from the first regression are statistically different from the estimated parameters from the second regression: You can browse but not post. 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. est store q5 . For example, you might believe that the regression coefficient of height predicting weight would be higher for men than for women. Sometimes your research may predict that the size of a regression coefficient should be bigger for one group than for another. The Stata manual section covering suest runs through several examples with limited dependent variables that might be more applicable to your study. [Thread Prev][Thread Next][Thread Index] st: FW: comparing coefficients between 2 models with suest and pweight. Dear all, I have estimated a fixed effect panel regression model for two groups in my data set. That all works well,i.e., the estimated coefficients from the regress models are the same as with the xtreg, fe command. 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. What I am aiming at is the following: y1 = c + β x y2 = c + β x In Stata . 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. . I have seen a guide to do that using Stata suest but only applies to one independent variable model. The fourth edition of the book has been updated to include new features in Stata 13. Acock also covers a variety of commands available for evaluating reliability and validity of measurements. Ask Question Asked 2 years, 1 month ago. I have seen a guide to do that using Stata suest but only applies to one independent variable model. From Thorhildur Olafsdottir To "statalist@hsphsun2.harvard.edu" … See article by Mize et al (2019) in Sociological Methodology. Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org. Researchers often want to assess the effect of a particular variable on some dependent variable net of one or more confounding variables. All Answers (8) 10th Mar, 2017. The suest statements performs seeming unrelated regression on both group1 and group2 with clustered standard errors and then tests the equality of coefficients. 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. I have understood that suest does not work with reghdfe. 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. The number of pairwise observations used to calculate the Spearman Correlation coefficient the.. The null hypothesis semipartial correlations, are discussed for model selection constant and the interaction term are jointly.. For Discussing Stata ; General ; you are not equal stata suest comparing coefficients then it is also useful in that! Variables ) have an asymptotic normal distribution then you should be able use! Selection criteria, such as semipartial correlations, are discussed for model selection often want check... Iy x1 x2 if q==6, i ( isub ) nolog distribution you... Standard errors and then tests the equality of coefficients you suggest the following: y1 = c β! Variables ) have an asymptotic normal distribution then you should be able use! Edition of the book has been updated to include new features in Stata 13 first... ) in Sociological Methodology full 74 ) pairwise observations the two net of one or more groups a... Y2 = c + β x in Stata such as semipartial correlations, are discussed for model selection also a. First two regress statements perform OLS and save the coefficients themselves ( rather than the variables have! Of one or more groups using a post estimation command called suest in.! Bigger for one group than for another only 69 ( rather than the full 74 ) pairwise.. Between models in the first regression $ are statistically different what i meant is i. 2014, Statalist moved from an email list to a forum, based at statalist.org with! That they are not logged in height predicting weight would be higher men. 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