35. Simulation Models in the Analysis of Panel Data — New Ways of Predictive Theory Formation in Longitudinal Social Research

1991 ◽  
pp. 581-600
Keyword(s):  
Panel Data ◽  
Social Research ◽  
Simulation Models ◽  
Theory Formation ◽  
Predictive Theory

scholarly journals How bad could it be? Worst-case bounds on bias in multistate models due to unobserved transitions

2021 ◽  
pp. 004912412199554
Author(s):  
Christian Dudel ◽  
Daniel C. Schneider
Keyword(s):  
Panel Data ◽  
Life Expectancy ◽  
Health Behaviors ◽  
Social Research ◽  
Good Health ◽  
Multistate Models ◽  
Worst Case ◽  
Typical Application ◽  
Retirement Study ◽  
The U.S

Multistate models are often used in social research to analyze how individuals move between states. A typical application is the estimation of the lifetime spent in a certain state, like the lifetime spent in employment, or the lifetime spent in good health. Unfortunately, the estimation of such quantities is prone to several biases. In this paper, we study the bias due to the often implicitly used assumption that there are no unobserved transitions between states. This assumption does often not hold for the panel data typically used to estimate multistate models, as the states occupied by individuals are only known at specific points in time, and further transitions between panel waves are not recorded. We present partially identified estimates of the lifetime spent in a state, or worse-case bounds, which show the maximum possible level of bias due to unobserved transitions. We provide two examples studying the lifetime spent in disability (disabled life expectancy; DLE). The first example applies our methods to results on cohort trends in DLE in the U.S. taken from Crimmins et al. (2009). In the second example, we replicate findings from Mehta and Myrskylä (2017), and apply our methods to data from the U.S. Health and Retirement Study (HRS) in order to estimate the effects of health behaviors on DLE.

scholarly journals Theory Construction Methodology: A practical framework for theory formation in psychology

2020 ◽  
Author(s):  
Denny Borsboom ◽  
Han van der Maas ◽  
Jonas Dalege ◽  
Rogier Kievit ◽  
Brian Haig
Keyword(s):  
Formal Model ◽  
Scientific Research ◽  
Simulation Models ◽  
Theory Construction ◽  
Theory Formation ◽  
University Curriculum ◽  
Improve Theory ◽  
Explanatory Adequacy ◽  
Mutualism Model ◽  
Model Equations

This paper aims to improve theory formation in psychology by developing a practical methodology for constructing explanatory theories: Theory Construction Methodology (TCM). TCM is a sequence of five steps. First, the theorist identifies empirical phenomena to become the target of explanation. Second, the theorist constructs a proto-theory: a set of theoretical principles that potentially explain these phenomena. Third, the proto-theory is used to construct a formal model: a set of model equations or simulation models that encode the explanatory principles. Fourth, the theorist investigates this model’s explanatory adequacy. This is done by formalizing the empirical phenomena in terms of the model, and assessing whether the model indeed reproduces them. Fifth, the theorist studies the overall adequacy of the theory by evaluating whether phenomena are indeed reproduced faithfully, whether explanatory principles are parsimonious and substantively plausible, and whether the theory implies new predictions to promote further research. We illustrate TCM with an example taken from the intelligence literature (the mutualism model of intelligence), discuss the place of TCM in the larger scheme of scientific research, and propose an outline for a university curriculum that can systematically educate psychologists in the process of theory formation.

scholarly journals PENGARUH VARIABEL MAKRO EKONOMI DAN HARGA MINYAK DUNIA TERHADAP INDUSTRI HALAL

2020 ◽  
Vol 6 (9) ◽  
pp. 1840
Author(s):  
Ali Mahdy Arrosikh ◽  
Ilmiawan Auwalin
Keyword(s):  
Exchange Rate ◽  
Data Analysis ◽  
Panel Data ◽  
World Bank ◽  
Inflation Rate ◽  
Social Research ◽  
Panel Data Analysis ◽  
Oil Price ◽  
Training Centre ◽  
And Training

This paper aims to discover the influence of inflation rate, exchange rate, global’s oil price and FDI toward halal industry in 48 OIC’s member Countries. This research uses data by Statistical, Economic and Social Research and Training Centre for Islamic Countries (Sesric), world bank and Thomas Reuters with quantative approach and were analyzed by using panel data analysis. According to the result it is have positive significant influence to the halal industry in 48 OIC Countries. Inflation rate have a significant positive influant; exchange rate have a non significant positive influant; global’s oil price have a significant negative influant; and FDI have a non-significant negative influant toward the increasing of the unemployment rate in 48 OIC’s Countries.Keywords: Halal Industry, Inflation, Exchange Rate, Global’s Oil Price, FDI

Correlation of Pore Structure and Permeability by SEM-Image Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 428-429
Author(s):  
C. A. Callender ◽  
Wm. C. Dawson ◽  
J. J. Funk
Keyword(s):  
Image Analysis ◽  
Pore Structure ◽  
Imaging System ◽  
Pore Space ◽  
Simulation Models ◽  
Image Analyzer ◽  
Imaging Data ◽  
Sem Images ◽  
Thin Sections ◽  
Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

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