Methodological Preliminaries

2020 ◽  
pp. 20-28
Author(s):  
Richard Breen
Keyword(s):  
Linear Models ◽  
Descriptive Statistics ◽  
Educational Expansion ◽  
Relative Mobility ◽  
Log Linear ◽  
Social Fluidity

All the country chapters in this volume use the same set of methods, and this chapter explains them in simple and accessible terms. These methods include descriptive statistics for the analysis of absolute mobility, the use of log-linear models for the analysis of relative mobility or social fluidity, and simulations to assess the role played by educational equalization and educational expansion in shaping trends in social fluidity.

Major social transformations and social mobility: the case of the transition to and from communism in Eastern Europe

1999 ◽  
Vol 38 (3) ◽  
pp. 463-491 ◽  
Author(s):  
Henryk Domański
Keyword(s):  
Eastern Europe ◽  
Social Mobility ◽  
Linear Models ◽  
Occupational Mobility ◽  
Relative Mobility ◽  
Social Transformations ◽  
Political Transformations ◽  
Log Linear ◽  
Communist Countries ◽  
Social Fluidity

This analysis compares the effects on social mobility of the political transformations in Eastern Europe which took place in the 1950s and the 1990s. The author examines absolute and relative mobility rates in Bulgaria, the Czech Republic, Hungary, Poland, Russia and Slovakia based on data from national random samples taken in 1993 and 1994. Log-linear models are applied to mobility tables for four periods, 1948-52, 1952-63, 1983-88 and 1988-93, to determine change in the strength of association between occupational categories. Searching for the effect of the transition to communism the author compares occupational mobility between 1948 and 1952 with occupational mobility between 1952 and 1963. In order to assess the effect of the transition from communism, mobility between 1983 and 1988 is compared to mobility between 1988 and 1993. It was definitely the transition to communism in the late 1940s that released the more intensive flows between basic segments of the social structure compared to what occurred during the exit from communism in the 1990s. Using both the diagonals and the constant social fluidity models, the author finds no evidence of increasing openness in post-communist countries. Contrariwise, in the 1948-63 period some significant change occurred in relative mobility chances. The conclusion is that the “first transformation” gave rise to a turn in social fluidity on the “genotypical” level.

Latency models: the statistical analysis of response times

1982 ◽  
Vol 12 (3) ◽  
pp. 659-665 ◽  
Author(s):  
Graham Dunn ◽  
Din Master
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Linear Models ◽  
Response Times ◽  
Descriptive Statistics ◽  
Failure Times ◽  
Log Linear

SYNOPSISThis paper introduces statistical methods suitable for the analysis of response, survival or failure times and, in particular, latencies measured in experiments on the speed of recall of memories. The discussion includes the use of simple descriptive statistics, as well as an explanation of the role of linear-logistic and log-linear models.

Education and Social Fluidity in Contemporary Italy

2020 ◽  
pp. 196-223
Author(s):  
Carlo Barone ◽  
Raffaele Guetto
Keyword(s):  
Twentieth Century ◽  
Significant Decline ◽  
Postwar Period ◽  
Relative Mobility ◽  
Men And Women ◽  
Economic Miracle ◽  
Educational Participation ◽  
Logistic Regressions ◽  
Log Linear ◽  
Social Fluidity

In this chapter we assess whether changes in educational participation have fostered changes in social fluidity in Italy over the twentieth century. By means of log-linear unidiff models and of multinomial logistic regressions, we show that a significant decline of schooling inequalities during the so-called economic miracle fueled an increase in social fluidity, in a context where the association between education and class destinations weakened only slightly. Direct inheritance also declined to some extent in the postwar period. These equalizing trends occurred for both men and women, but were stronger among women, and involved primarily, though not exclusively, the agricultural classes. However, all these trends have flattened out in the youngest cohorts, where social fluidity is highly inertial. Since the process of occupational upgrading has halted in recent decades, the recent stability of relative mobility involves also the stagnation of absolute mobility.

When and why are log-linear models self-normalizing?

2015 ◽  
Author(s):  
Jacob Andreas ◽  
Dan Klein
Keyword(s):  
Linear Models ◽  
Log Linear

Log-Linear Models with Dependent Spatial Data

1983 ◽  
Vol 15 (6) ◽  
pp. 801-813 ◽  
Author(s):  
B Fingleton
Keyword(s):  
Spatial Data ◽  
Statistical Models ◽  
Linear Models ◽  
Square Lattice ◽  
Categorical Variables ◽  
Systematic Sampling ◽  
Pairwise Correlations ◽  
Independent Observations ◽  
Intersection Points ◽  
Log Linear

Log-linear models are an appropriate means of determining the magnitude and direction of interactions between categorical variables that in common with other statistical models assume independent observations. Spatial data are often dependent rather than independent and thus the analysis of spatial data by log-linear models may erroneously detect interactions between variables that are spurious and are the consequence of pairwise correlations between observations. A procedure is described in this paper to accommodate these effects that requires only very minimal assumptions about the nature of the autocorrelation process given systematic sampling at intersection points on a square lattice.

Educational Homogamy Among Married and Unmarried Couples in Europe

2008 ◽  
Vol 30 (1) ◽  
pp. 28-52 ◽  
Author(s):  
Dana Hamplova
Keyword(s):  
Linear Models ◽  
Married Couples ◽  
European Social Survey ◽  
Social Survey ◽  
Educational Homogamy ◽  
Educational Barriers ◽  
Educational Groups ◽  
Institutional Contexts ◽  
Using Data ◽  
Log Linear

In this article, educational homogamy among married and cohabiting couples in selected European countries is examined. Using data from two waves (2002 and 2004) of the European Social Survey, this article compares three cultural and institutional contexts that differ in terms of institutionalization of cohabitation. Evidence from log-linear models yields two main conclusions. First, as cohabitation becomes more common in society, marriage and cohabitation become more similar with respect to partner selection. Second, where married and unmarried unions differ in terms of educational homogamy, married couples have higher odds of overcoming educational barriers (i.e., intermarrying with other educational groups).

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