Contents
Can a country be an independent variable in a regression?
Alternatively, to get more accurate statistical tests, you could skip weighting and enter country dummy variables as independent variables in your model. But the latter solution presupposes that the associations between dependent and independent variables are constant across countries, which is frequently not the case.
What’s the difference between the two approaches to pooling data?
The difference between these two approaches is that we are constraining the variance of the residual to be the same in the two groups when we pool the data. When we estimated separately, we estimated y = β01 + β11×1 + β21×2 + ( β02 – β01) g2 + ( β12 – β11) g2x1 + ( β22 – β21) g2x2 + u, u ~ N (0, σ 2 )
Can You pool data without constraining residual variance?
Pooling data without constraining residual variance We can pool the data and estimate an equation without constraining the residual variances of the groups to be the same. Previously we typed and we start exactly the same way.
How to pool data in linear regression in Stata?
The dataset has 74 observations for group=1 and another 71 observations for group=2. Using these data, I can run the regressions separately by typing I did that in Stata, and it let me summarize the results. When I typed command [1], I obtained the following results (standard errors in parentheses):
Can a multilevel model of country effect be reliable?
With large sample sizes of individuals within each country but only a small number of countries, analysts can reliably estimate individual-level effects but estimates of parameters summarizing country effects are likely to be unreliable. Multilevel modelling methods are no panacea.
Which is the best method to estimate country effects?
Researchers often wish to estimate ‘country effects’ on socio-economic outcomes of individuals. The most popular quantitative approach is regression analysis of harmonized data from multiple countries in which individual-level outcomes are modelled as a function of both individual-level and country-level characteristics (observed and unobserved).
How often is regression analysis of multilevel data used?
The popularity of regression analysis of multilevel country data is illustrated by the European Sociological Review . Of the 340 articles published between 2005 and 2012, approximately 75 exploit multilevel data sets with individual respondents within countries.