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	<title>BookPasta.net &#187; Statistics</title>
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	<link>http://bookpasta.net</link>
	<description>and eBookz for all</description>
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		<title>Design of Observational Studies</title>
		<link>http://bookpasta.net/blog/2010/01/18/design-of-observational-studies/</link>
		<comments>http://bookpasta.net/blog/2010/01/18/design-of-observational-studies/#comments</comments>
		<pubDate>Mon, 18 Jan 2010 21:32:36 +0000</pubDate>
		<dc:creator>admin</dc:creator>
				<category><![CDATA[Econometrics]]></category>
		<category><![CDATA[Statistics]]></category>
		<category><![CDATA[observational study]]></category>
		<category><![CDATA[sensitivity analysis]]></category>

		<guid isPermaLink="false">http://bookpasta.net/?p=545</guid>
		<description><![CDATA[The concepts of causal inference in experiments and observational studies are introduced using the elementary mathematics of independent coin flips to determine treatment assignment The basic tools of multivariate matching – such as propensity scores, optimal matching, full matching, fine balance, risk set matching – are introduced with many examples and with reference to implementation in R The key source of uncertainty in an observational study is possible bias from covariates that were not measured. The ability of competing designs to separate treatment effects from unmeasured biases – that is, the design sensitivity – is discussed in detail for the first time in book form An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. Design of Observational Studies is divided [...]]]></description>
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		<title>Methods of Contemporary Mathematical Statistical Physics</title>
		<link>http://bookpasta.net/blog/2009/11/05/methods-of-contemporary-mathematical-statistical-physics/</link>
		<comments>http://bookpasta.net/blog/2009/11/05/methods-of-contemporary-mathematical-statistical-physics/#comments</comments>
		<pubDate>Thu, 05 Nov 2009 17:35:04 +0000</pubDate>
		<dc:creator>admin</dc:creator>
				<category><![CDATA[Statistics]]></category>
		<category><![CDATA[lattice]]></category>
		<category><![CDATA[metastability]]></category>
		<category><![CDATA[statistic]]></category>
		<category><![CDATA[stochastic]]></category>

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		<description><![CDATA[An introductory chapter on lattice spin models is useful as a background for other lectures of the collection. The topics include new results on phase transitions for gradient lattice models (with introduction to the techniques of the reflection positivity), stochastic geometry reformulation of classical and quantum Ising models, the localization/delocalization transition for directed polymers. A general rigorous framework for theory of metastability is presented and particular applications in the context of Glauber and Kawasaki dynamics of lattice models are discussed. A pedagogical account of several recently discussed topics in nonequilibrium statistical mechanics with an emphasis on general principles is followed by a discussion of kinetically constrained spin models that are reflecting important peculiar features of glassy dynamics. Written for: Researchers and graduate students]]></description>
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