Johannis Buxtorfii De abbreviaturis Hebraicis liber novus et copiosus : cui acc. operis Talmudici brevis recensio ... item Bibliotheca rabbinica nova, ordine alph. disposita

Text teilw. in hebr. Schr. und Sprache

Introductio in Orientem, sive Synopsis quaestionum nobiliorum de origine, natura, usu et adminiculis linguarum orientalium etplerarumque extra Europam : Ebraicae, Chaldaicae, Syriacae, Samaritanae ...; Item de Genuina Antiqvitate Punctorum Vocalium & Accentuum Ebraeorum ...

Wittenbergae, Univ., Diss., 1672

Entwicklung der Fünf-Item-Kurzskala STAI-SKD zur Messung von Zustandsangst

Das State-Trait-Angstinventar (STAI) ist eines der am häufigsten eingesetzten Erhebungsinstrumente im Bereich der Angstdiagnostik. Die STAI-Skala zur Erfassung von Zustandsangst umfasst 20 Items. Unter bestimmten Erhebungsbedingungen erweist es sich als relativ schwierig, eine große Menge an Items zu bearbeiten oder aber es steht nicht ausreichend Testzeit zur Verfügung. Daher war es das Ziel der vorliegenden Studie, eine Kurzform der State-Version des STAI zu entwickeln. An einer Stichprobe von N = 65 Studierenden wurde aufgrund inhaltlicher und statistischer Kriterien eine Kurzform der State-Version des STAI, das STAI-SKD, mit fünf Items generiert. Eine konfirmatorische Faktorenanalyse an einer zweiten Stichprobe von N = 191 Studierenden zeigte, dass das STAI-SKD die Angstkomponenten Emotionality und Worry abbildet. Die Beziehungen des STAI-SKD zu positivem und negativem Affekt sowie dessen Veränderungssensitivität fielen in einer dritten Stichprobe (N = 80 Studierende) erwartungsgemäß aus. Die neue Kurzform der State-Version des STAI erlaubt eine ökonomische Erfassung der Zustandsangst.

Ioannis Buxtorfii De Abbreviaturis Hebraicis Liber Novus Et Copiosus : Cui Accesserunt Operis Talmudici Brevis Recensio Eiusdemque Librorum & Capitum Index: Item Bibliotheca Rabbinica Ordine Alphabetico Disposita Cum Adpendice Eidem Inserta

Teilw. in hebr. Schr.

Modeling absolute differences in life expectancy with a censored skew-normal regression approach.

Parameter estimates from commonly used multivariable parametric survival regression models do not directly quantify differences in years of life expectancy. Gaussian linear regression models give results in terms of absolute mean differences, but are not appropriate in modeling life expectancy, because in many situations time to death has a negative skewed distribution. A regression approach using a skew-normal distribution would be an alternative to parametric survival models in the modeling of life expectancy, because parameter estimates can be interpreted in terms of survival time differences while allowing for skewness of the distribution. In this paper we show how to use the skew-normal regression so that censored and left-truncated observations are accounted for. With this we model differences in life expectancy using data from the Swiss National Cohort Study and from official life expectancy estimates and compare the results with those derived from commonly used survival regression models. We conclude that a censored skew-normal survival regression approach for left-truncated observations can be used to model differences in life expectancy across covariates of interest.

Ms. germ. fol. 3 - Historia arcana oder Beheime Verzeichnüß von Martino Luthero und Philippo Melanchthone item Von denen drey Churfürsten zu Sachsen Johann Friedrichen, Moritzen und Augusto

Alte Signatur: II,49

Optimally Combining Censored and Uncensored Datasets

Economists and other social scientists often face situations where they have access to two datasets that they can use but one set of data suffers from censoring or truncation. If the censored sample is much bigger than the uncensored sample, it is common for researchers to use the censored sample alone and attempt to deal with the problem of partial observation in some manner. Alternatively, they simply use only the uncensored sample and ignore the censored one so as to avoid biases. It is rarely the case that researchers use both datasets together, mainly because they lack guidance about how to combine them. In this paper, we develop a tractable semiparametric framework for combining the censored and uncensored datasets so that the resulting estimators are consistent, asymptotically normal, and use all information optimally. When the censored sample, which we refer to as the master sample, is much bigger than the uncensored sample (which we call the refreshment sample), the latter can be thought of as providing identification where it is otherwise absent. In contrast, when the refreshment sample is large and could typically be used alone, our methodology can be interpreted as using information from the censored sample to increase effciency. To illustrate our results in an empirical setting, we show how to estimate the effect of changes in compulsory schooling laws on age at first marriage, a variable that is censored for younger individuals. We also demonstrate how refreshment samples for this application can be created by matching cohort information across census datasets.

Diomedis Grammatici Opvs, Ab Ioanne Caesario, ita emendatum, scholijsq[ue] illustratum, ut nulla porrò labes insideat. Item Donati De Octo Orationis partibus, & barbarismo libellus, ab eodem recognitus. Cum Indice

Fingerprint nach Ex. der HAAB Weimar und der UB Frankfurt

Ms. lat. oct. 32 - De sinibus, chordis et arcubus, item instrumento revelatore secretorum, c. 1 - 9

Vorbesitzer: Simon Jacob