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X-WR-CALDESC:Events for California Center for Population Research
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DTSTART;TZID=America/Los_Angeles:20171024T140000
DTEND;TZID=America/Los_Angeles:20210423T170000
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SUMMARY:Sander Greenland\, UCLA Department of Epidemiology
DESCRIPTION:The UCLA Department of Statistics and the Center for Social Statistics presents:\nStatistical Significance and Discussion of the Challenges of Avoiding the Abuse of Statistical Methodology\nSander Greenland will offer his perspective on the paper\, “Redefine Statistical Significance”\, which was the topic of the previous week’s seminar. Also he will discuss the challenges of avoiding the abuse of statistical methodology. \nSpeaker:\nSander Greenland\, Professor Emeritus\, UCLA Department of Epidemiology
URL:https://ccpr.ucla.edu/event/sander-greenland-ucla-department-of-epidemiology/
CATEGORIES:CSS Events
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DTSTART;TZID=America/Los_Angeles:20171108T153000
DTEND;TZID=America/Los_Angeles:20210423T170000
DTSTAMP:20210424T024124Z
CREATED:20210424T024124Z
LAST-MODIFIED:20210424T024124Z
UID:10000738-1510155000-1619197200@ccpr.ucla.edu
SUMMARY:Hadley Wickham\, RStudio
DESCRIPTION:The UCLA Department of Statistics and the Center for Social Statistics presents:\nProgramming data science with R & the tidyverse\nTidy evaluation is a new framework for non-standard evaluation that\nwill be used throughout tidyverse. In this talk\, I’ll introduce you to\nthe problem that tidy eval solves\, illustrated with examples of the\nvarious approaches used in R. I’ll then explain the most important\ncomponents so that you can start writing your own functions instead of\ncopying and pasting tidyr and dplyr code. I’ll finish with a small\nshiny app that shows how tidy eval is a natural fit for handling user\ninput. \nHadley Wickham\, RStudio\nhttp://hadley.nz/
URL:https://ccpr.ucla.edu/event/hadley-wickham-rstudio/
CATEGORIES:CSS Events
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DTSTART;TZID=America/Los_Angeles:20180206T140000
DTEND;TZID=America/Los_Angeles:20210423T170000
DTSTAMP:20210424T025431Z
CREATED:20210424T025431Z
LAST-MODIFIED:20210424T025431Z
UID:10000739-1517925600-1619197200@ccpr.ucla.edu
SUMMARY:Per Block\, ETH Zurich (Swiss Federal Institute of Technology in Zurich)
DESCRIPTION:The UCLA Department of Statistics and the Center for Social Statistics presents:\nModelling Mobility Tables as Weighted Networks\nContemporary research on occupational mobility\, i.e. how people move between jobs\, tends to view mobility as being mostly determined by individual and occupational characteristics. These studies focus on people’s sex\, ethnicity\, age\, education or class origin and how they get access to jobs of different wages\, working conditions\, desirability\, skill profiles and job security. Consequently\, observations in occupational mobility tables are understood as independent of one another\, which allows the use of a variety of well-developed statistical models. As opposed to these “classical” approaches focussed on individual and occupational characteristics\, I am interested in modelling and understanding endogenously emerging patterns in occupational mobility tables. These emergent patterns arise from the social embedding of occupational choices\, when occupational transitions of different individuals influence each other. To analyse these emergent patterns\, I conceptualise a disaggregated mobility table as a network in which occupations are the nodes and connections are made of individuals transitioning between occupations.\n\n\nIn this paper\, I present a statistical model to analyse these weighted mobility networks. The approach to modelling mobility as an interdependent system is inspired by the exponential random graph model (ERGM); however\, some differences arise from ties being weighted as well as from specific constraints of mobility tables. The model is applied to data on intra-generational mobility to analyse the interdependent transitions of men and women through the labour market\, as well as to understanding the extent to which clustering in mobility can be modelled by exogenously defined social classes or through endogenous structures.\n  \nPer Block\, ETH Zurich (Swiss Federal Institute of Technology in Zurich)\nsite
URL:https://ccpr.ucla.edu/event/per-block-eth-zurich-swiss-federal-institute-of-technology-in-zurich/
CATEGORIES:CSS Events
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