"The Silk Roads are the symbol of the interconnectedness of ancient Eurasian civilizations. Using challenging land and maritime routes, merchants and adventurers, diplomats and missionaries, sailors and soldiers, and camels, horses and ships, carried their commodities, ideas, languages and pathogens enormous distances across Eurasia. The result was an underlying unity that traveled the length of the routes, and which is preserved to this day, expressed in common technologies, artistic styles, cultures and religions, even disease and immunity patterns"--
From 1200 BCE to 900 CE, the world witnessed the rise of powerful new states and empires, as well as networks of cross-cultural exchange and conquest. Considering the formation and expansion of these large-scale entities, this fourth volume of The Cambridge World History outlines key economic, political, social, cultural, and intellectual developments that occurred across the globe in this period. Leading scholars examine critical transformations in science and technology, economic systems, attitudes towards gender and family, social hierarchies, education, art, and slavery. The second part of the volume focuses on broader processes of change within western and central Eurasia, the Mediterranean, South Asia, Africa, East Asia, Europe, the Americas and Oceania, as well as offering regional studies highlighting specific topics, from trade along the Silk Roads and across the Sahara, to Chaco culture in the US southwest, to Confucianism and the state in East Asia
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In: Craig , B M , de Bekker-Grob , E W , González Sepúlveda , J M & Greene , W H 2021 , ' A Guide to Observable Differences in Stated Preference Evidence ' , Patient . https://doi.org/10.1007/s40271-021-00551-x
BACKGROUND AND OBJECTIVE: In health preference research, studies commonly hypothesize differences in parameters (i.e., differential or joint effects on attribute importance) and/or in choice predictions (marginal effects) by observable factors. Discrete choice experiments may be designed and conducted to test and estimate these observable differences. This guide covers how to explore and corroborate various observable differences in health preference evidence. METHODS: The analytical process has three steps: analyze the exploratory data, analyze the confirmatory data, and interpret and disseminate the evidence. In this guide, we demonstrate the process using dual samples (where exploratory and confirmatory samples were collected from different sources) on 2020 US COVID-19 vaccination preferences; however, investigators may apply the same approach using split samples (i.e., single source). RESULTS: The confirmatory analysis failed to reject ten of the 17 null hypotheses generated by the exploratory analysis (p < 0.05). Apart from demographic, socioeconomic, and geographic differences, political independents and persons who have never been vaccinated against influenza are among those least likely to be vaccinated (0.838 and 0.872, respectively). CONCLUSIONS: For all researchers in health preference research, it is essential to know how to identify and corroborate observable differences. Once mastered, this skill may lead to more complex analyses of latent differences (e.g., latent classes, random parameters). This guide concludes with six questions that researchers may ask themselves when conducting such analyses or reviewing published findings of observable differences.
