Think of a score of 1 as meaning that the government ought to reduce the income differences between rich and poor, and a score of 7 meaning that the government should not concern itself with reducing income differences. Others think that the government should not concern itself with reducing this income difference between the rich and the poor. In the example below I include the centered value of year in my models, but you get the same result if year is not included.114) Some people think that the government in Washington ought to reduce the income differences between the rich and the poor, perhaps by raising the taxes of wealthy families or by giving income assistance to the poor. The obvious upshot of this is that you get exactly the same standard errors if you use the design variable vstrat as the stratification variable or you create a new stratification variable to include year. International Statistical Review / Revue Internationale de Statistique, Vol. Duncan and Graham Kalton Issues of Design and Analysis of Surveys across Time. In this regard, readers might find Greg J. Princeton University Press for many examples of time trends. Social Trends in American Life: Findings from the General Social Survey Since 1972. There are few surveys that have been replicated over a period of more than 45 years.See Marsden, PV I(ed) 2012. Thus YEAR has been seen as a major variable of interest and not merely as a stratification variable.
#Gss 2014 codebook software#
As software for analysis of complex survey designs became widely available and as the survey became used for much more than teaching purposes investigators began to push for more sample design information and NORC has responded.Ī major rationale for the GSS has been the investigation of time trends, for example in attitudes toward abortion, capital punishment, gun control and many other variables.
Over time, the design has become increasingly complex to the point where each biennial survey now contains a panel and a repeated cross sectional component.
Of course technically competent people understood that there was a design effect but for the purpose of undergraduate education it was ignored in part because software to handle the complex survey design was not available until much later in the game.
#Gss 2014 codebook code#
"self weighting." The code book and documentation were also kept relatively simple. It was intended to be a basic data set for undergraduate education and as a basis for "social indicators" research and was deliberately kept simple, e.g. The first couple of years used quote sampling. The GSS dates back to 1972 at which time things were, relative to to what we do now, much simpler. Bulletin of the International Statistical Institute, Contributed Papers 2, 103-104. Weights for combining surveys across time or space. Note also this interesting article about weighting for multi-year analysis.Ĭhu, Adam, J Michael Brick, and Graham Kalton. However, the fact that the stratification changed in many years suggests that the super-stratum approach may be best. I haven't found any guidance about what to do for GSS. Or, rather, I've created "superstrata" that grouped year and year-specific strata. Multiple year surveys: When multi-year surveys draw independent sample in each year, I've always treated the years as strata. Appendix A of the codebook shows many changes over the years, including changes to the sampling frame and target population. but I see nothing about this in the Codebook for the combined data 1972-2014 (( ). Apparently GSS has switched to a rotating panel design ( ). I have a suspicion it won't matter much either way, but I wonder if there is any consensus or controversy over whether or not to do this. On the one hand, the advice to treat year as a stratum variable sounds reasonable on the other hand I don't remember seeing similar advice anywhere else. Instead, I include dummies for Year in my models. My current analysis uses svyset without year as a stratum variable. I haven't seen this approach recommended before, and am not sure if this is the best route to take. This code is similar to the UCLA code you sent me, with the addition of year (see ). He writes that "it is reasonable to treat Year as the stratum variable because the surveys from each year are independent, and Year is a fixed variable." His code to set up pooled GSS data is: svyset sampcode, strata(year). Do you have an opinion on treating Year as a stratum variable with pooled data? I ask because Donald Treiman recommends this in his book Quantitative Data Analysis.
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