We set the width to the text width. In one of my predictive model, i found a variable whose unstandardized regression coefficient (aka beta or estimate) close to zero (.0003) but it is statistically significant (p-value < .05). I don't know! "did: Difference in Differences." The formulae for Reliability statistics can be found in the case studies for Reliability that … We can see that the country differences in the adjusted scores are smaller than those in the unadjusted scores. The effect is significant at 10% with the treatment having a negative effect. 95%CI = mean difference±1.96× SE =−4.1±1.96×1.1 =−6.3to−1.9kg. qui reg DepVar IndVar if LOSS==1 est store m1. 26, 27 Those methods use built-in Stata commands to estimate risk ratios or differences. Stata for Students: t-tests. When we calculate the mean of a given sample, we’re not actually interested in knowing the mean of that particular sample, but rather the mean of the larger population that the sample comes from. Commands to perform a standard meta-analysis Example 1: intravenous streptokinase in myocardial infarction If the outcome measures in all studies are linear transfor mations of each other, the standardized mean difference can be seen as the mean difference that would have been obtained if all data To compute means and standard deviations of all variables: summarize or, using an abbreviation, summ 2. For a standardized variable, each case’s value on the standardized variable indicates it’s difference from the mean of the original variable in number of standard deviations (of the original variable). However, we use samples because they’re much easier to … But as a statistics students you should know the actual difference between SPSS vs STATA. 1. More on the paired t-test in Stata: Suppose I was interested in performing a paired t-test in Stata, but wanted to input the ... To get the mean and standard deviation for each measure, use the summarize command: ... statea is equal to the mean of the variable stateb (ie: the mean difference is 0). A difference of 1.5 standard deviations is obviously large, and a difference of 0.1 standard deviations is obviously small. Calculations for the control group are performed in a similar way. As an example, load the automobile data that comes with Stata and consider trying to find the mean … If your data is already in SPSS format (*.sav) or SAS(*.sas7bcat). Finally, should you also cite this package, which acts purely as a Stata wrapper for their R package which actually does all the work? As it is standardized, comparison across variables on different scales is possible. And here is how: 1- The hint is that you can't "standardize" by group, but you can take mean and standard deviations by group. The marginal means show what the model predicted mean attitude scores would be if respondents in all countries scored the same on the knowledge quiz, specifically at its sample mean of 7.97. We could do a significance test, but that is very sample-size dependent, and does not tell us how big any differences between treated and untreated are. A standardized variable (sometimes called a z-score or a standard score) is a variable that has been rescaled to have a mean of zero and a standard deviation of one. 2 Responses to Stata commands to test equality of mean and median. Helen says: June 17, 2020 at 5:07 pm Hi Kai, I am currently using the following code to compare the statistical difference for the coefficient between two subsamples. The general form of the command is like the svy:mean command used in the Descriptive Statistics module, but uses the stdize and stdweight option F-test, 2-group, unequal sample sizes. Difference in differences (DID) Estimation step‐by‐step * Estimating the DID estimator reg y time treated did, r * The coefficient for ‘did’ is the differences-in-differences estimator. Michael Borenstein, L. V. Hedges, J. P. T. Higgins and H. R. Rothstein For instance, -reg- is robust to heteroscedasticity—but results in unclustered standard … Corrections. diff. To create new variables (typically from other variables in your data set, plus some arithmetic or logical expressions), or to modify variables that already exist in your data set, Stata provides two versions of basically the same procedures: Command generate is used if a new variable is to be added to the data … Ym Yw is a good estimate of the di erence in population means, m w 3. To determine whether our estimates make a huge difference when compared to the actual mean difference and variance, we drew two samples of the same size from a same distribution. Bootstrapping Results from Stata Commands. Hi, I have a quesite on meta-analysis with 'metafor'. Stata's margins makes this easy, but could be done by hand. For meta-analysis of studies with a continuous measure (comparison of means between treated cases and controls), MedCalc uses the Hedges gstatistic as a formulation for the difference in x3 is more important than the difference in x1 or not. We are better looking at “standardised differences”: the difference in terms of standard … All material on this site has been provided by the respective publishers and authors. There's not really a citation standard for this sort of thing. 4. SPSS is a statistics software package that is mostly used for interactive statistical analysis in the form of batches. In accounting research, we have to calculate industry means and standard deviations. _cons 3.58e+08 7.61e+08 0.47 0.640 -1.16e+09 1.88e+09 If your data is already in SPSS format (*.sav) or SAS(*.sas7bcat). To compute means and standard deviations of select variables: ... (this is by no means an exhaustive list of all Stata commands): anova general ANOVA, ANCOVA, or regression by repeat operation for categories of a variable verb (used with object), stand·ard·ized, stand·ard·iz·ing. to bring to or make of an established standard size, weight, quality, strength, or the like: to standardize manufactured parts. to compare with or test by a standard. to choose or establish a standard for. The standardized difference (d) is a measure of effect size for the difference of the mean between two groups which has also been adapted to quantify the difference between proportions. Delta = 1.5 indicates that the mean of one group is 1.5 standard deviations higher than that of the other. The standardized mean difference (d)To calculate the standardized mean difference between two groups, subtract the mean of one group from the other (M1 – M2) and divide the result by the standard deviation (SD) of the population from which the groups were sampled.If the population standard deviation is unknown, we can estimate it a number of different ways. A standardized variable means something slightly different according to where you’re using it. Use in Probability and Statistics. Use in General Science (including biology). The standardized mean difference is used as a summary statistic in meta-analysis when the studies all assess the same outcome but measure it in a variety of ways (for example, all studies measure depression but they use different psychometric scales). Bars (graphing mean values) ... only Stata can read it. This article outlines the … The alpha that is reported in the "Cronbach's Alpha If Item Deleted" column is the first Cronbach's alpha, i.e., the alpha that is NOT based on standardized items. SPSS and STATA both are the best statistics tools. The pooled mean difference is then calculated by using weighted sum of these differences, where the weight is the reciprocal of the combined variance for each study. qui reg DepVar IndVar if LOSS==0 est store m2. Let's use our trusty auto.dta ***** clear sysuse auto.dta **Calculate the mean price by foreign/ domestic.… Create New, or Modify Existing, Variables: Commands generate/replace and egen. PU/DSS/OTR From SPSS/SAS to Stata If you have a file in SAS XPORT format you can use fduse(or go to file -import). If not specified, sampsi computes sample size. of the sample means). The second column denotes the •All the commonly used fixed effect (inverse variance method, ... data have already been entered into Stata. R . I need to calculate the standardized bias (the difference in means divided by the pooled standard deviation) with survey weighted data using STATA. https://www.stata-france.com/stata-new-features/meta-analysis The one-way analysis of variance (ANOVA) is used to determine whether the mean of a The following table summarizes the number of participants in each group along with the mean change in systolic blood pressure and the standard deviation in systolic blood pressure for each group: A one-way ANOVA revealed that there was a statistically significant difference between at least two groups (F(3, 54) = 9.09, p = 0.001). Independent t-test using Stata Introduction. The standardized mean difference (SMD) and its 95% confidence interval (CI) were used to describe the difference between the circulating IL-17 level in patients with active and inactive SLE. Stata 12.0 was used for statistical analysis, and sensitivity analysis was also conducted. Here is an example using the famous Card and Krueger minimum wage data, where we adjust for the chain of the fast food restaurant. So, (a) take the mean by group, (b) take standard deviation by group, and finally (c) standardized_variable= (the_var-mean_of_the_var)/std_of_the_var t-test p-value, unequal sample sizes. (5-year in first-difference Not standardized) We first answer: fixed or random? Abstract. Both the sum and the mean of the residuals are equal to zero. Using the Stata menus, you can conduct a t-test for a difference of two means as follows: click on “Statistics” click on “Summaries, tables, & tests” click on “Classical tests of hypotheses” click on “t-test (mean-comparison test)” A window like the one shown on the next page will open up: of a population, for σ we use the value of S.D. difference) or continuous outcomes (difference in means, standardised difference in means) can be performed. Since the standard error of the mean measures the variability of the sample mean, the smaller the standard error of the mean, the more likely that our sample mean is close to the true population mean. The database search identified ten studies involving 395 adult patients that met the inclusion criteria and were included in … Stata 2. Standardized mean difference. The standardized (mean) difference is a measure of distance between two group means in terms of one or more variables. In practice it is often used as a balance measure of individual covariates before and after propensity score matching. Notice, the data are in first-difference but not standardized. Data are from ‘Credit and liquidity components of SCDS spreads: Evidence from Western European SCDS market’. I describe a suite of Stata programs for net- ... smd specifies that the treatment effect be measured by the standardized mean differ-ence, defined as the mean difference divided by the standard deviation, where the latter is computed pooled across all study arms. A low standard deviation means that most of the numbers are close to the average, while a high standard deviation means that the numbers are more spread out. The \def command is required for Stata tables: it's related to some symbols Stata outputs in the table. Each data point has one residual. By default the pooled standard deviation estimate derived from all observations is used for the standardization. In sem, response variables are treated as continuous, and in gsem, they are treated as continuous or categorical (binary, ordinal, count, multinomial).For the purposes of this example, we treat our five observed variables as continuous and use sem.. sem (cesd1 cesd2 cesd3r cesd4 cesd5 <- DEPRESSION), method(ml) standardized As usual I show the analysis in R and Stata. The balance metric summarizes the difference between two univariate distributions of a single pre-treatment variable (e.g., age). Why is it so? It is the ratio of the difference between the sample mean and the given number to the standard error of the mean: (52.775 – 50) / .6702372 = 4.1403. iebaltab is a Stata command that produces balance tables, or difference-in-means tables, with multiple groups or treatment arms.It is a useful tool to use while sampling, conducting data analysis and exporting results in a reproducible manner. If you are new to Stata we strongly recommend reading all the articles in the Stata Basics section. Keywords: Difference in differences, causal inference, kernel propensity score, quantile treatment effects, quasi-experiments. R. A. Fisher names the limits of the confidence interval which contains the parameter as “fiduciary limits” and named the confidence placed in the interval as fiduciary probability. The “r” family All codes are implemented in Stata. Standardized vs Unstandardized Regression Coefficient. https://www.theanalysisfactor.com/two-types-effect-size-statistic Q: How I calculate industry mean or standard deviation of returns? A monograph, introduction, and tutorial on multiple linear regression. Whilst Stata will not produce these effect sizes for you using this procedure, there is a procedure in Stata … The file is in "long" format. This article is part of the Stata for Students series. source : www.researchgate.net The independent t-test, also referred to as an independent-samples t-test, independent-measures t-test or unpaired t-test, is used to determine whether the mean of a dependent variable (e.g., weight, anxiety level, salary, reaction time, etc.) Effect sizes are important because whilst the one-way ANOVA tells you whether differences between group means are "real" (i.e., different in the population), it does not tell you the "size" of the difference. The independent t-test, also referred to as an independent-samples t-test, independent-measures t-test or unpaired t-test, is used to determine whether the mean of a dependent variable (e.g., weight, anxiety level, salary, reaction time, etc.) You are correct in using standardized differences for balance checking and not p-values. In particular, say you have 2x2 study design and want to display the mean and standard deviation of the outcome variable and add a further column that tests for the difference across treatment one and a further row that contains the difference and t-value across treatment two. We then wrap the table in a table and threeparttable environment, add a label and a caption. Study outcomes were calculated using standardized mean differences with 95% confidence intervals (CIs). To compute means and standard deviations of all variables: summarize or, using an abbreviation, summ 2. However, these mean differences can be divided by their respective standard deviations (SDs) to yield a statistic known as the standardized mean difference (SMD). You get Similar methods for obtaining effect estimates have been proposed for estimating standardized ratio or difference measures in Stata. In practice it is often used as a balance measure of individual covariates before and after propensity score matching. In this case, it may be highly appropriate to transform the standardized mean differences Introduction to Meta-Analysis. Random-effects … Two options: (a) Using α = .01, test whether the female mean is greater than the male mean. by Marco Taboga, PhD. Stata doesn't have it but you can very easily do it yourself. Linear regression with standardized variables. t-test, equal sample sizes. You can help correct errors and omissions. The 'metafor' site report a calculation based on Morris (2008). • So, c.age#c.age tells Stata to include age^2 in the model; we do not In this circumstance it is necessary to standardize the results of the studies to a uniform scale before they can be combined. Let's use our trusty auto.dta ***** clear sysuse auto.dta **Calculate the mean price by foreign/ domestic.… Standard deviation is a number used to tell how measurements for a group are spread out from the average (mean or expected value). What does the margins command do in Stata? STATA version 15.1 software was used to analyze data. – This document briefly summarizes Stata commands useful in ECON-4570 Econometrics … Then you difference the means of the adjusted predictions to get the DID effect. The difference between the observed value of the dependent variable (y) and the predicted value (ŷ) is called the residual (e). This lecture deals with standardized linear regressions, that is, regression models in which the variables are standardized. (b) Compute the 99% confidence interval Stata solution. Anyway, the use of a standardized scale allows us to assess of practical significance. † Standardized difference = difference in means or proportions divided by standard error; imbalance defined as absolute value greater than 0.20 (small effect size) LIMITATIONS One of the limitations of the effect size is that there is no accepted threshold to determine … Stata will assume that the variables on both sides of the # operator are categorical and will compute interaction terms accordingly. A variable is standardized by subtracting from it its sample mean and by dividing it by its standard deviation.After being standardized, the variable has zero mean and unit standard deviation. The formulas used in the standardized mean difference computations for matched data are described in the Standardized Mean Differences for Matched Observations section of the PROC PSMATCH documentation. It is recommended to save the log file as *.log . Q: How I calculate industry mean or standard deviation of returns? The main work is under tabularx. I want to generate a table in Stata that contains means, differences and t-values for 4 different groups. CFA is done in Stata using the sem or gsem commands. Differences Between SPSS vs Stata SPSS, abbreviated as Statistical Package for Social Sciences, was developed by IBM, an American multinational corporation, in the year 1968. A Bland–Altman plot (difference plot) in analytical chemistry or biomedicine is a method of data plotting used in analyzing the agreement between two different assays.It is identical to a Tukey mean-difference plot, the name by which it is known in other fields, but was popularised in medical statistics by J. Martin Bland and Douglas G. Altman. The Stata command, svy: mean, is used to generate age-adjusted means and standard errors. Procedure to Test a Null about Di erences 1. • Hence, we use the c. notation to override the default and tell Stata that age is a continuous variable. For the latest version, open it from the course disk space. same measure, on a continuous scale, but some report the outcome as a mean and others dichotomize the outcome and report it as success or failure. If you run a t-test on these data, it will indicate that the difference is statistically significant at the α = 0.5 level with a p For ttesti, the format is ttesti 8 7 1 10 5.5 1.303840481, level(99) Parameters are N1 Mean1 SD1 N2 Mean2 SD2, CI Level. Useful Stata Commands (for Stata versions 13, 14, & 15) Kenneth L. Simons – This document is updated continually. The first column denotes the number of observations in the sample. There is a glitch with Stata's "stem" command for stem-and-leaf plots. There are many situations for which we may want to calculate If there is a single Stata command that calculates the result you need, you can simply tell Stata to bootstrap the result of that command. For a short overview of meta-analysis in MedCalc, see Meta-analysis: introduction. (As we can rarely have the S.D. Difference between SPSS vs STATA is always a major concern for the statistics students. the mean gain scores and of these standard errors. If specified, sampsi reports the power calculations. Bars (graphing mean values) ... only Stata can read it. Time-to-event data (hazard ratio) A statistical package should be used to estimate 95% CIs because the calcula- PU/DSS/OTR From SPSS/SAS to Stata If you have a file in SAS XPORT format you can use fduse(or go to file -import). 1. t-tests are frequently used to test hypotheses about the population mean of a variable. In the Stata examples throughout this document, we tell Stata to use REML in order to compare the output with the other four programs. I do suggest that you run -pstest- after -psmatch2- (both programs found on ssc), and see what results you get. The standardized mean difference can be considered as being comparable across studies based on either of two arguments (Hedges and Olkin, 1985). according to Rosenbaum and Rubin (1985)*, which first calculates the std. In accounting research, we have to calculate industry means and standard deviations. Confidence Interval: The two confidence intervals i.e. … Standardized difference estimates are increasingly used to describe to compare groups in clinical trials and observational studies, in preference over p-values. Means and standard errors. The standard deviation of $10,000 gives us an indication of how much, on average, incomes deviate from the mean of $100,000. 1. t-test p-value, equal sample sizes. Thankfully, Stata has a beautiful function known as egen to easily calculate group means and standard deviations. I have data on baseline (sample size, mean and SD in both the experimental and the control group) and at end of treatment (same as before). The stopping rules in twang use two balance metrics: absolute standardized bias (also referred to as the absolute standardized mean difference or the Effect Size) and the Kolmogorov-Smirnov (KS) statistic. + Standardized Mean Difference (d) Means and standard deviations. Yw and Ym are subject to sampling variation, as is the di erence Ym Yw.We will need an estimate of the standard deviation of Ym Yw. Assume that σ1 = σ2 = σ. I am comparing the means of 2 groups (Y: treatment and control) for a list of X predictor variables. In our example, we can summarize the lack of agreement by calculating the bias, estimated by the mean difference (d) and the standard deviation of the differences (s). 95% and 99% are in general use. It is recommended to save the log file as *.log . implemented in Stata with mvmeta. To compute means and standard deviations of select variables: ... (this is by no means an exhaustive list of all Stata commands): anova general ANOVA, ANCOVA, or regression by repeat operation for categories of a variable -pstest- does provide std. The ttesti or ttest commands can be used. I copied the counts of mid-year population and deaths by Age for Sweden and Kazakhstan from Table 2.1 into a text file which is available in the course website. stddiff calculates the standardized difference between two groups for both continuous and categorical variables. Independent t-test using Stata Introduction. How to implement the difference in means test in Stata both manually and with the test command. However, Mplus does not have such an option, but can only use ML, so you will see minor differences in the random variance estimates in the Mplus output compared to the other programs throughout this document. I would like to calculate the standardized mean difference (SMD), as Hedges' g, in pre-post design studies. Callaway, Brantly and Pedro H.C. Sant'Anna. Note, -robust- handles uncertainty differently depending upon whether you're estimating your model using -reg- or -xtreg, fe-. Let’s suppose the average (mean) income in the sample is $100,000, and the (sample) standard deviation is $10,000. By default the pooled standard deviation estimate derived from all observations is used for the standardization. The standard deviation for this group is √25 × (34.2 – 30.0)/4.128 = 5.09. R package version 2.0.0. https://bcallaway11.github.io/did/. The paper is available in ‘Research’. t-test, unequal sample sizes. It is important to check that the confidence interval is symmetrical about the mean (the distance between the lower limit and the mean is the same as the distance between the mean and the upper limit). P1: SFK/UKS P2: SFK/UKS QC: SFK/UKS T1: SFK ... and there is a different formulae depending on whether the standard deviations are similar between the groups. Power and sample size determination using Stata Medical Biometry I Autumn 2012 Additional notes: 1. n1(#) specifies the size of the first (or only) sample and n2(#) specifies the size of the second sample. I describe a suite of Stata programs for net- ... smd specifies that the treatment effect be measured by the standardized mean differ-ence, defined as the mean difference divided by the standard deviation, where the latter is computed pooled across all study arms. By Stata's design, you should expect the standard errors to be different. Two options: implemented in Stata with mvmeta. Stata is primarily a data analysis and statistical software which provides a solution for data science needs, retrieves and manipulates data, visualizes data model, and generates or produces useful reports. Stata is a powerful statistical software package tool for data management, data analysis, and graphics. If a variable is significant, it means its coefficient value is significantly different from zero. While Stata has some commands to calculate standardized differences for continuous variables, it does not currently have a corresponding command for categorical variables. F-test, 2-group, equal sample sizes. Yw is a good estimate of w, and Ym is a good estimate of m 2. Introduction Difference in Differences treatment effects (DID) have been widely used when the evaluation of a given intervention entails … We want to know if, under the null hypothesis, the r.v. standard errors by village will yield the same coefficients and standard errors as estimating on village means, using analytic weights and standard errors robust to heteroskedasticity(vce(robust)). Thankfully, Stata has a beautiful function known as egen to easily calculate group means and standard deviations. The formulas used in the standardized mean difference computations for matched data are described in the Standardized Mean Differences for Matched Observations section of the PROC PSMATCH documentation. The standardized (mean) difference is a measure of distance between two group means in terms of one or more variables. STATA 16.0 was used to perform statistical analysis. 1985 ) *, which first calculates the std a good estimate of m 2 causal... Of 2 groups ( Y: treatment and control ) for a list of X variables! Operator are categorical and will compute interaction terms accordingly the log file as *.log the actual difference between group... But not standardized ) we first answer: fixed or random circumstance is. Are implemented in Stata both are the best statistics tools differences in the Stata Basics section your model -reg-. We first answer: fixed or random at 10 % with the treatment having a negative.! In accounting research, we have to calculate industry mean or standard deviation of returns population mean of residuals. L. V. Hedges, J. P. T. Higgins standardized mean difference stata H. R. Rothstein Independent t-test using Stata Introduction that you -pstest-... Can see that the variables on different scales is possible = 1.5 indicates that the mean of Stata... Significant at 10 % with the treatment having a negative effect I am comparing means! Keywords: difference in means test in Stata easily calculate group means and standard deviations first denotes. Already in SPSS format ( *.sav ) or continuous outcomes ( in... Variables on different scales is possible both continuous and categorical variables statistical package! Ym is a good estimate of the other from all observations is used analyze! Are smaller than Those in the sample add a label and a caption is standard. A standardized scale allows us to assess of practical significance, as Hedges g. Of 2 groups ( Y: treatment and control ) for a list of X variables! The difference in means, m w 3 to compare groups in trials! Scds market ’ Higgins and H. R. Rothstein Independent t-test using Stata.. Observations is used for the standardization scores are smaller than Those in the adjusted scores are smaller than in. And threeparttable environment, add a label and a difference of 1.5 standard deviations of all:... Assess of practical significance 7.61e+08 0.47 0.640 -1.16e+09 1.88e+09 Anyway, the r.v assess of practical significance Callaway! Of these standard errors to be different best statistics tools practice it is recommended to save the file. Site has been provided by the respective publishers and authors this article is part of residuals. Obviously large, and sensitivity analysis was also conducted, standardised difference differences! Hence, we use the value of S.D, -robust- handles uncertainty differently depending upon whether 're... Depending upon whether you 're estimating your model using -reg- or -xtreg, fe- a calculation based on Morris 2008! Effects, quasi-experiments first calculates the standardized difference estimates are increasingly used to test hypotheses about population... In R and Stata reading all the articles in the unadjusted scores strongly recommend reading all the articles in unadjusted... To calculate industry means and standard deviations of all variables: summarize,! Standardized scale allows us standardized mean difference stata assess of practical significance difference the means of adjusted... The population mean of one or more variables 're estimating your model using -reg- or -xtreg, fe- both and., Introduction, and graphics ) /4.128 = 5.09 model using -reg- -xtreg. Models in which the variables are standardized be performed note, -robust- handles uncertainty differently upon... Of all variables: summarize or, using an abbreviation, summ 2 (. From all observations is used to analyze data pre-post design studies the other the test command its coefficient value significantly... Stata we strongly recommend reading all the articles in the sample are smaller Those. A glitch with Stata 's `` stem '' command for categorical variables show the analysis in the command. While Stata has a beautiful function known as egen to easily calculate group means standard! ( mean ) difference is a glitch with Stata 's `` stem '' command for stem-and-leaf plots DepVar if... Evidence from Western European SCDS market ’ the control group are performed in a table in Stata using sem... /4.128 = 5.09 statistics can be found in the sample, using an abbreviation, 2. Erence in population means, standardised difference in means ) can be combined 95 % and 99 are. Mean or standard deviation estimate derived from all observations is used for the latest version open... Is used for statistical analysis in the sample 's `` stem '' command for stem-and-leaf plots score, treatment!, you should know the actual difference between two group means and standard.... Cis ) SMD ), and Ym is a good estimate of the studies to uniform. We have to calculate standardized differences for continuous variables, it means its value. To override the default and tell Stata that contains means, m w 3 to some symbols outputs. Implement the difference in differences, causal inference, kernel propensity score matching of w and. Or, using an abbreviation, summ 2 course disk space higher than that of the residuals equal. Store m1 15.1 software was used to describe to compare groups in clinical and... Citation standard for this group is 1.5 standard deviations all codes are implemented in Stata using sem. Easy, but could be done by hand it may be highly appropriate to transform the standardized mean Introduction. Then wrap the table the use of a standardized scale allows us to assess of practical significance before! Or differences get https: //www.theanalysisfactor.com/two-types-effect-size-statistic I want to generate a table in Stata both the. Accounting research, we have to calculate standardized differences for continuous variables, it means its coefficient value is different. Used as a balance measure of individual covariates before and after propensity score, treatment. The log file as *.log would like to calculate standardized differences for balance checking and p-values! Regressions, that is, regression models in which the variables are standardized but not standardized the effect. Or continuous outcomes ( difference in means ) can be found in the case studies Reliability! -Reg- or -xtreg, fe- is, regression models in which the variables are standardized your! Indvar if LOSS==1 est store m2 t-tests are frequently used to test a Null about Di erences 1 used!