Outlines of lectures on materia medica and botany :delivered in Jefferson Medical College, Philadelphia /by William P.C. Barton.

v.2 (1827)

Outlines of lectures on materia medica and botany :delivered in Jefferson Medical College, Philadelphia /by William P.C. Barton.

v.1 (1827)

Vegetable materia medica of the United States, or, Medical botany :containing a botanical, general, and medical history of medicinal plants indigenous to the United States. Illustrated by coloured engravings, made after drawings from nature, done by the author /by William P.C. Barton.

v. 1

Vegetable materia medica of the United States, or, Medical botany :containing a botanical, general, and medical history of medicinal plants indigenous to the United States. Illustrated by coloured engravings, made after drawings from nature, done by the author /by William P.C. Barton.

v. 2

The human genetic mutant cell repository : list of genetic variants, chromosomal aberrations and normal cell cultures submitted to the repository / Institute for Medical Research, Camden, New Jersey.

4th ed.

Collaboration strategies and technological innovation: a contractual perspective of the relationship between firms and techonological centers

In this paper, a theoretical framework for analyzing the selection of governance structures for implementing collaboration agreements between firms and Technological Centers is presented and empirically discussed. This framework includes Transaction Costs and Property Rights’ theoretical assumptions, though complemented with several proposals coming from the Transactional Value Theory. This last theory is used for adding some dynamism in the governance structure selection. As empirical evidence of this theoretical explanation, we analyse four real experiences of collaboration between firms and one Technological Center. These experiences are aimed to represent the typology of relationships which Technological Centers usually face. Among others, a key interesting result is obtained: R&D collaboration activities do not need to always be organized through hierarchical solutions. In those cases where future expected benefits and/or reputation issues could play an important role, the traditional more static theories could not fully explain the selected governance structure for managing the R&D relationship. As a consequence, these results justify further research about the adequacy of the theoretical framework presented in this paper in other contexts, for example, R&D collaborations between firms and/or between Universities or Public Research Centers and firms.

The period function of the generalized Lotka-Volterra centers

"Vegeu el resum a l'inici del document del fitxer adjunt"

Modeling usage of medical care services: the medical expenditure panel survey data, 1996-2000

We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required.

Likelihood-based approaches to modeling demand for medical care

We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.