Hello everyone
Last chance to register for the upcoming 2-day Instats seminar Multilevel
SEM in Mplus: Location-Scale Models
<https://instats.org/seminar/multilevel-location-scale-models-group-7685>
running March 1-3. This seminar is coupled with a free on-demand workshop
introducing Multilevel SEM, representing a $400 value.
If you've wanted to expand your research skills so that you can specify and
estimate models that incorporate variances at higher levels of analysis,
then this workshop is for you! We'll be covering how group variances can be
used as controls, indicators, and moderators within a variety of models. We
will also explore common pitfalls and estimation issues you will encounter,
and through a variety of hands-on examples we'll see how to overcome these
difficulties.
Also, don't miss out on our upcoming seminars on Advanced Panel Data
Modeling
<https://instats.org/seminar/advanced-panel-data-modeling-with-stata3776>
(March 2-3), Hierarchical Linear Models (HLM) and Multilevel Causal
Inference
<https://instats.org/seminar/hierarchical-linear-models-hlm-and-mul6120>
with prof Stephen Raudenbush (March 9-10), Introduction to Continuous Time
Structural Equation Modeling
<https://instats.org/seminar/introduction-to-continuous-time-structur8917>
(March 15-17), and Survey Design and Analysis
<https://instats.org/seminar/measurement-modeling-designing-and-anal9866>
(March 15-17). These are filling up quickly so make sure you and your
colleagues/PhD students don't miss out!
Best wishes and happy modeling!
Michael Zyphur
Director
Institute for Statistical and Data Science
<https://u25630606.ct.sendgrid.net/ls/click?upn=nVdQE-2B8Stia1M6tUcM07RVQbRGyiFw0h18oRmOjW-2Feum7T2l44a0i3R-2BmE1SHmR0pdI82L9a8egSFf9sH8iUK-2FtF9pGRh1xtKxELQPim19d1oaBqI9cK1nIgWPU8WUEGWx5h_ukItYw4utsc-2BPJXOIs3muiWFkNLFxvzVjRDcRdGParWYcWpjz4bDfIxRcVZFwz2hbchU49RjchvJbIEZfuhAU1tO8tQXbdWu5jQei0rx1H597CbzM4Zg2wwFMQ9ZBeFJDGwkvoSL-2BcvD4bazfwYAxP-2FK2sM3Y-2FHu5XHydh-2F2MhzlHcC-2B0neBxDffrLZzsHX56s1pdhxvXDext0FAw7j5K-2BWbnqV065sn6-2BRrrsk6-2BbV4ACfxroXKmmRy9QfTUbLJQLaXhDSrOYTM-2FWHKDTdY78u-2BE4LvaEyrenEIkUxxyaH5-2Bq2aPwZ6atRIQYPRdn2OU-2BJkXX2iNhGq7UFCB-2Fl-2BAn-2BPvJ-2BK79u09BzzqVfDa-2F-2FFpBf9AyKwCslnuQr7cTix2H-2FuDUyxv0YGzmDoBcF80pXIrFKWz-2BUYEPOwLYChJvjIPK-2FOqSjSrpfJGgDKveaXYHr-2FkC5hn5m6IUXZkOZqIldIIix5XCtPM7DhGBKLIkdhhoJ5TxLt1rv4RzzfLgbFfCwf1HFBlmXXGJevFYXrOvHBdgX7e743YxXhPa-2BBwqDilF6y9o0QnBRTJsKtzkKj>
*in**stats.org* <http://instats.org>
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