Despite the growing number of statistical analyses of life-history data and a long tradition of biographical research, there is often no communication between these two streams of life-course research. It is possible to examine the life course quantitatively through life histories, which may be used to model synthetic biographies in order to reveal patterns in the timing and sequencing of life events, the durations of states between them, and the causal links between them. It is also possible to examine the life course qualitatively through life stories, e.g. biographical narratives, which reflect how persons understand, experience and attach meaning to events and states in their life. Through a quantitative analysis of life-history data we can describe and explain the morphology of particular events in the observed population, while a qualitative analysis of biographical narratives provides insight into people’s decision-making, perceptions of their options, and how they attach meanings to and experience events. This article summarizes the strengths and weaknesses of both approaches, explains in which sense they are connected or differentiated from each other, what data and analyses each perspective may utilize, and briefly introduces one type of mixed methods life course research that utilizes the complementarity of both approaches., Hana Hašková a Radka Dudová., and Obsahuje bibliografii
The article briefly describes multilevel models and presents their simplest applications. After the methodological and statistical need for this procedure is explained, real data are used to demonstrate how a hierarchical linear model is constructed. The article presents models with a random intercept, models with random slopes, and models with explanatory variables measured at higher levels. In the conclusion, other possible applications of multilevel analysis are discussed, and the basic readings on multilevel analysis are presented.
This article focuses on methods for measuring corruption, first describing three generations of corruption indicators and then comparing them qualitatively and quantitatively. Corruption is a clandestine activity that is extremely difficult to measure; there are no official statistics on the number of corruption cases. For this reason, corruption can only be measured indirectly, by various proxies, and it is extremely hard to state whether these indicators are reliable and indeed measure the corruption phenomena in a given country. A large number of different indicators have been developed over the years that try to capture and quantify corruption. Some authors measure perceptions of corruption, others try to use “hard data” to explore the level of corruption in a country, and even others combine different measurements, weight them, and then publish composite indicators to capture the overall level of corruption in a country. This article aims to evaluate the quality of the different indicators using quantitative and qualitative methods. Possible uses and value of each individual indicator are discussed in terms of quality and practical considerations. First-generation indicators combine expert evaluations, surveys, and other data on corruption. The article focuses on the two best-known and most frequently used indicators - the Control of Corruption measurement by the World Bank and the Corruption Perception Index by Transparency International. Second-generation indicators are based on opinion surveys that ask respondents about their perceptions of and own experience with corruption. There are two types of such surveys, one focusing on the public and the other one on businesses. The second-generation indicators include surveys such as Eurobarometer, World Values Survey (WVS), European Social Survey (ESS), Global Corruption Barometer (GCB), WB BEEPS, or International Social Survey Programme (ISSP). Finally, the author presents a correlation analysis of different indicators over time and across countries, indicating whether and how strongly these three generations correlate with one another. The article concludes with a discussion on whether the three generations of indicators measure the same type of corruption and whether they can be used interchangeably. As for results, it seems that there are statistically significant associations between different types of indicators; however, this significance is, in most cases, not high enough to allow for interchangeability. Therefore, it is of utmost importance to carefully select the type of indicator used for scientific research, as results and conclusions might differ significantly depending on the indicator used., Kristýna Bašná., and Obsahuje bibliografické odkazy
The aim of this article is to present a specific method for the study of the life-course, which focuses on life-course trajectories as a whole through the use of sequence analysis. In the first part, two approaches for the quantitative analysis of the life-course are distinguished: an event-oriented perspective and a trajectory-based (holistic) perspective. The holistic perspective is based on sequence analysis and more specifically on optimal matching. The trajectory-based perspective does not focus on single life events, but on whole sequences of events. In the second part, using the Czech wave of the ISSP 2002 dataset, which includes partnership and family histories, this article presents several examples of the use of sequence analysis of family trajectories. This study shows that sequence analysis can help identify patterns associated with typical and distinctive life-course trajectories., Jana Chaloupková., and Obsahuje bibliografii a bibliografické odkazy