Micro-macro multilevel latent class models with multiple discrete individual-level variables

An existing micro-macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the individual-level data are summarized at the group-level by constructing a discrete latent variable at the group level and this group-level latent variable is used as a predictor for the group-level outcome. In the first extension, that is referred to as the Direct model, the multiple individual-level variables are directly used as indicators for the group-level latent variable. In the second extension, referred to as the Indirect model, the multiple individual-level variables are used to construct an individual-level latent variable that is used as an indicator for the group-level latent variable. This implies that the individual-level variables are used indirectly at the group-level. The within- and between components of the (co)varn the individual-level variables are independent in the Direct model, but dependent in the Indirect model. Both models are discussed and illustrated with an empirical data example

Expanding the methodological toolbox of HRM researchers:The added value of latent bathtub models and optimal matching analysis

Researchers frequently rely on general linear models (GLMs) to investigate the impact of human resource management (HRM) decisions. However, the structure of organizations and recent technological advancements in the measurement of HRM processes cause contemporary HR data to be hierarchical and/or longitudinal. At the same time, the growing interest in effects at different levels of analysis and over prolonged periods of time further drives the need for HRM researchers to differentiate from traditional methodology. While multilevel techniques have become more common, this article proposes two additional methods that may complement the current methodological toolbox of HRM researchers. Latent bathtub models can accurately describe the multilevel mechanisms occurring in organizations, even if the outcome resides at the higher level of analysis. Optimal matching analysis can be useful to unveil longitudinal patterns in HR data, particularly in contexts where HRM processes are measured on a continuous basis. Illustrating the methods’ applicability to research on employee engagement, this paper demonstrates that the HRM community—both research and practice—can benefit from a more diversified methodological toolbox, drawing on techniques from within and outside the direct field to improve the decision-making process

Surpassing Simple Aggregation: Advanced Strategies for Analyzing Contextual-Level Outcomes in Multilevel Models

This article introduces two advanced analytical strategies for analyzing contextual-level outcomes in multilevel models: the multilevel SEM and the two-step approach. Since these strategies are seldom used in comparative survey research, we first discuss their methodological and statistical advantages over the more commonly applied approach of group mean aggregation. We then illustrate these advantages in an empirical analysis of the effect of citizens' support for democratic values at the individual level on a contextual-level outcome - the persistence of democracy - drawing on data from the World Values Survey and the Quality of Government project. Whereas we found no significant effect of support for democratic values in the model using simple group mean aggregation, citizens' support for democratic values was a significant predictor of democracies' estimated survival rate when applying latent aggregation in multilevel SEM and the two-step approach. The article corroborates previous concerns with simple aggregation and demonstrates how researchers can improve the validity of their analyses of contextual-level outcomes by using alternative strategies of aggregation

Multilevel models for cross-national comparisons: the association between individual and national-level demographic characteristics in fertility and partnerships

Multilevel models are increasingly used in social sciences and demography to both account for clustering within higher level aggregations and evaluate the interaction between individual and contextual information. While this is justifiable in some studies, the extension of multilevel models to national level analysis- and particularly cross-national comparative analysis- is problematic and can hamper the understanding of the interplay between individual and country level characteristics. This paper proposes an alternative approach, which allocated countries to classes based on economic, labour market and policy characteristics. Classes influence the profiles of three key demographic behaviours at a sub-national level: marriage, cohabitation and first birth timing. Individual data are drawn from a subset of the Harmonized Histories dataset, and national level information from the GGP contextual database. In this example, three country classes are extracted reflecting two Western patterns and an Eastern pattern, divided approximately along the Hajnal line. While Western countries tend to exhibit higher levels of family allowances albeit accounting for a lower share of spending which is associated with lower marriage and later fertility, Eastern countries generally show a higher share of spending but at lower absolute levels with lower cohabitation rates and early fertility

Micro-macro multilevel analysis of day-to-day lifestyle and carbon emissions in UK multiple occupancy households

Far-reaching changes in daily life present a pressing need to balance energy consumption with environmental impact. Previous research on household carbon emissions generally described its contributors in disposable income, consumption pattern, and household-related lifestyle, whereas they have not fully explored how carbon emissions relate to residents' day-to-day lifestyles. Given that individual lifestyles within a household may be correlated, there is a need to disentangle the clustering effect of household members' lifestyles and their association with household carbon emissions. This study used micro-macro multilevel modelling to examine the structure of individual lifestyles and their impact on household carbon emissions for 8618 multiple occupancy households of 19,816 respondents in the UK Household Longitudinal Study dataset. The results showed that a factor capturing energy-saving lifestyle behaviours significantly reduced housing fuel use emissions and a second capturing transportation and consumption choices cut motor emissions. Interestingly, the contribution of energy-saving lifestyle in cutting down housing-fuel-using emissions becomes more pronounced when household income and household characteristics (e.g., household size, dwelling, house ownership, number of cars, urbanity, employment) were controlled for. Contrarily, the strength of green transportation and consumption lifestyle contributing to lower motor emissions was weakened after controlling for household characteristics. Findings indicated that day-to-day lifestyle not only reflects individual variability in sustainable living but also systematic household variation in carbon emissions. Knowledge of which living patterns are responsible for disproportionately high levels of carbon emissions can enhance effective targeted policy aimed at stimulating sustainable lifestyles and carbon reduction

Latent class models for cross-national comparisons:the association between individual & national-level characteristics in fertility & partnership

Multilevel modelling techniques such as random models or fixed effect are increasingly used in social sciences and demography to both account for clustering within higher level aggregations and evaluate the interaction between individual and contextual information. While this is justifiable in some studies, the extension of multilevel models to national level analysis — and particularly cross-national comparative analysis — is problematic and can hamper the understanding of the interplay between individual and country level characteristics. This paper proposes an alternative approach, which allocates countries to classes based on economic, labour market and policy characteristics. Classes influence the profiles of three key demographic behaviours at a sub-national level: marriage, cohabitation and first birth timing. Woman level data are drawn from a subset of the Harmonized Histories dataset, and national level information from the GGP contextual database. In this example, three country classes are extracted reflecting two Western patterns and an Eastern pattern, divided approximately along the Hajnal line. While Western countries tend to exhibit higher levels of family allowances albeit accounting for a lower share of spending which is associated with lower marriage and later fertility, Eastern countries generally show a higher share of spending but at lower absolute levels with lower cohabitation rates and early fertility

Latent class models for cross-national comparisons:the association between individual & national-level characteristics in fertility & partnership

Multilevel modelling techniques such as random models or fixed effect are increasingly used in social sciences and demography to both account for clustering within higher level aggregations and evaluate the interaction between individual and contextual information. While this is justifiable in some studies, the extension of multilevel models to national level analysis — and particularly cross-national comparative analysis — is problematic and can hamper the understanding of the interplay between individual and country level characteristics. This paper proposes an alternative approach, which allocates countries to classes based on economic, labour market and policy characteristics. Classes influence the profiles of three key demographic behaviours at a sub-national level: marriage, cohabitation and first birth timing. Woman level data are drawn from a subset of the Harmonized Histories dataset, and national level information from the GGP contextual database. In this example, three country classes are extracted reflecting two Western patterns and an Eastern pattern, divided approximately along the Hajnal line. While Western countries tend to exhibit higher levels of family allowances albeit accounting for a lower share of spending which is associated with lower marriage and later fertility, Eastern countries generally show a higher share of spending but at lower absolute levels with lower cohabitation rates and early fertility