does men and woman have the same betas). est store q5 . Also, you can compare marginal effects. In Stata you can use suest and test to do it. 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). 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. Race is of course nominal, and income and age are binned as well, but I treat the income bins as a linear effect. qui xtlogit Iy x1 x2 if q==5,i(isub) nolog . * oglm replication of Allison’s Table 2, Model 2 with interaction added: 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) You can browse but not post. . Number of obs: This is the number of pairwise observations used to calculate the Spearman Correlation Coefficient. It's the block of code from suest down that I cannot figure out in SAS. Dear all, I have estimated a fixed effect panel regression model for two groups in my data set. See article by Mize et al (2019) in Sociological Methodology. Search in General only Advanced Search Search. 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: . Because there were some missing values for the variable rep78, Stata used only 69 (rather than the full 74) pairwise observations. The most important, it … stata gsem standardized coefficients, of effect sizes and standardized coefficients. I want to test if $\beta$ and $\omega$ are statistically different. The fourth edition of the book has been updated to include new features in Stata 13. I have understood that suest does not work with reghdfe. Comparing Logit & Probit Coefficients…Richard Williams, ASA 2012 Page 5 In Stata, heterogeneous choice models can be estimated via the user-written routine oglm. The first two regress statements perform OLS and save the coefficients, which I know how to do in SAS. 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. All Answers (8) 10th Mar, 2017. From Thorhildur Olafsdottir To "statalist@hsphsun2.harvard.edu" … 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. One is comparing the same model with different samples (e.g. Login or Register. gsem is a very flexible command that allows us to fit very sophisticated models. Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org. Statistical methods are developed for comparing regression coefficients between models in the setting where one of the models is nested in the other. Test equality between coefficients in STATA. est store q6 . 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. 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 wonder if that is possible to compare coefficients between two multivariate regression model? 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. That all works well,i.e., the estimated coefficients from the regress models are the same as with the xtreg, fe command. Solution 2: Try suest. 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. > 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. What I am aiming at is the following: y1 = c + β x y2 = c + β x In Stata . > > Unfortunately, y is truncated in my data and z is a dummy and thus a probit > will > be a better choice. If the coefficients themselves (rather than the variables) have an asymptotic normal distribution then you should be able to use t-tests. 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. This is, in effect, testing if the estimated parameters from the first regression are statistically different from the estimated parameters from the second regression: 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. For example, you might believe that the regression coefficient of height predicting weight would be higher for men than for women. Researchers often want to assess the effect of a particular variable on some dependent variable net of one or more confounding variables. Cite. We can compare the regression coefficients among these three age groups to test the null hypothesis. 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). Sometimes your research may predict that the size of a regression coefficient should be bigger for one group than for another. On Statalist you suggest the following: "What I meant is that I can think of two main uses for -suest-. Is there any other way to compare between male and female parameters? 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. Acock also covers a variety of commands available for evaluating reliability and validity of measurements. I am trying to compare the coefficients of two panel data regressions with the same dependent variable. Notice that the constant and the coefficient on x are exactly the same as in the first regression. Home; Forums; Forums for Discussing Stata; General; You are not logged in. I have seen a guide to do that using Stata suest but only applies to one independent variable model. 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. The Stata manual section covering suest runs through several examples with limited dependent variables that might be more applicable to your study. qui xtlogit Iy x1 x2 if q==6,i(isub) nolog . Spearman’s rho: This is the Spearman correlation coefficient. 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). I estimate them using the STATA command reg2hdfe with cluster at individual level. If you concluded that they are not equal, then it is obvious from inspection that sranklow is the bigger of the two. I wonder if that is possible to compare coefficients between two multivariate regression model? 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. And I want to test if the coefficients are significantly different for both group. 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. It seems that 'suest' command does not work with 'xtreg'. Log in with; Forums ; FAQ; Search in titles only. 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 found that 'suest ' of Stata is a very useful command for comparing regression coefficients between different (separated) regression models EASILY. Here is a simple way to test that the coefficients on the dummy variable and the interaction term are jointly zero. Comparing the coefficients between models does not suggest substantial differences. I am trying to use Suest to compare the coefficients of a regressor in two regressions ran on two different datasets. xtreg y1 x i.z xtreg y2 x i.z I want to check whether the βs are significantly different. I would normally use suest but it is not possible with reg2hdfe. 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. Various selection criteria, such as semipartial correlations, are discussed for model selection. If the models were multinomial logistic regressions, you could compare two or more groups using a post estimation command called suest in stata. 2. between the quantiles (using sqreg). Re: Comparing coefficient across two xtmixed (growth curve) models Hi Lance, You could try a (pseudo-) multivariate model. Comparing fixed effects coefficients between two groups 14 Apr 2017, 14:20. [Thread Prev][Thread Next][Thread Index] st: FW: comparing coefficients between 2 models with suest and pweight. However, it is also useful in situations that involve simple models. (Also, note that if you use non-linear transformations or link functions (e.g., as in logistic, poisson, tobit, etc. Now, conduct the Chow Test using the .test command. Stata: Data Analysis and Statistical Software . 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