Social indicators and psychiatric admission rates: a case-register study in the Netherlands

1991 ◽  
Vol 21 (1) ◽  
pp. 177-184 ◽  
Author(s):  
Sjoerd Sytema
Keyword(s):  
Relative Risk ◽  
Social Indicators ◽  
The Other ◽  
Logit Models ◽  
Need For Care ◽  
Psychiatric Admission ◽  
Case Register ◽  
Independent Variables ◽  
Admission Rates ◽  
The Relationship

SYNOPSISEnvironmental as well as individual socio-demographic and illness characteristics are related to the risk of admission. This paper addresses the problem of the interrelationships of these factors to admission rates. Using the Groningen Psychiatric Case Register, admission rates (during 1986 and 1987) from 34 administrative areas were calculated. Logit models were fitted in order to test the relationship between the relative risk of being admitted and sex, age, marital status, diagnosis, urbanization and distance from facilities. The effect of urbanization remains under the control of the other independent variables. The concept of ‘need for care’, related to ‘true’ and ‘treated’ incidence, is discussed.

Social indicators and the prediction of psychiatric admission in different diagnostic groups

1997 ◽  
Vol 171 (5) ◽  
pp. 457-462 ◽  
Author(s):  
Anthony P. Boardman ◽  
Richard E. Hodgson ◽  
Martyn Lewis ◽  
Keith Allen
Keyword(s):  
Regression Models ◽  
Psychotic Disorders ◽  
Social Indicators ◽  
Strong Correlations ◽  
Psychiatric Admission ◽  
Admission Rates ◽  
Neurotic Disorders ◽  
Positive Correlations ◽  
Using Data

BackgroundRecent findings indicate that the established association between social indicators of deprivation and psychiatric admission rates may not hold across all diagnoses.MethodAdmission rates in individuals aged 16–64 years for 71 electoral wards in North Staffordshire were calculated for six diagnostic groups using data from the Korner Episode System for 1987–1993. These were correlated with selected individual census variables, Townsend and Jarman indices. The ability of regression models to predict admission rates was tested.ResultsThe strongest correlations were found for total admissions (r 0.44–0.79). Strong correlations were found for neurotic disorders/depression (r 0.29–0.62), schizophrenia (r 0.24–0.59), all non-psychotic disorders combined (r 0.41–0.71) and all psychotic disorders combined (r 0.33–0.67). Predicted admission rates for total admissions, psychotic and non-psychotic admissions using regression models showed strong positive correlations with observed admission rates.ConclusionsThe strong correlations between social indicators of deprivation and total psychotic admission rates are consistent with the results of previous studies. The strong associations between social indicators and admissions for non-psychotic disorders is contrary to previous findings and may be partly explained by the relatively high admission rates for neurotic disorders.

Do not group quantitative variables

2020 ◽  
pp. 219-222
Author(s):  
Bendix Carstensen
Keyword(s):  
Utility Function ◽  
The Other ◽  
Optimal Decision ◽  
Continuous Variables ◽  
Decision Point ◽  
Independent Variables ◽  
Optimal Decisions ◽  
The Relationship ◽  
Continuous Predictor ◽  
Predicted Risk

This chapter explores the problems caused by categorizing quantitative variables (here termed continuous variables). Optimum decisions are made by applying a utility function to a predicted value. At the decision point, one can solve for the personalized cutpoint for predicted risk that optimizes the decision. Dichotomization on independent variables is completely at odds with making optimal decisions. To make an optimal decision, the cutpoint for a predictor would necessarily be a function of the continuous values of all the other predictors. Moreover, categorization assumes that the relationship between the predictor and the response is flat within intervals; this assumption is far less reasonable than a linearity assumption in most cases. Categorization of continuous variables using percentiles is particularly hazardous. To make a continuous predictor be more accurately modelled when categorization is used, multiple intervals are required.

Residential Mobility in Dutch Housing Markets

1986 ◽  
Vol 18 (6) ◽  
pp. 763-788 ◽  
Author(s):  
W A V Clark ◽  
M C Deurloo ◽  
F M Dieleman
Keyword(s):  
Housing Market ◽  
Explanatory Power ◽  
Parameter Estimates ◽  
Logit Analysis ◽  
Logit Models ◽  
Independent Variables ◽  
Regional Effects ◽  
Relative Contribution ◽  
Dutch Housing ◽  
The Relationship

A one percent stratified random sample of all Dutch households (comprising 62 000 households) is used to examine mobility in the Dutch housing market. Two techniques, proportional reduction in uncertainty (PRU), and logit analysis are used to evaluate the relative contribution of independent variables in explaining mobility across the tenure types and by housing market regions. The PRU technique is used to select the best variables and to simplify the categories of those variables before logit analyses. Given a reduced set of variables and combinations of categories, logit models are utilized to provide parameter estimates of the contributions of the independent variables. The PRU technique shows that it is possible to make considerable simplifications in the combinations of categories for variables, and the logit models (for owners, public renters, and private renters) indicate distinct differences in the combinations of variables which are most appropriate in each of these sectors. In particular, the logit analysis shows that the relationship between age and mobility is almost linear, but between income and mobility it is curvilinear, and that evaluating interaction effects adds significantly to our understanding of the reason to move or to stay. The models show that it is necessary to treat the three tenure sectors separately, even though age, just as we expected, dominates all sectors in terms of its explanatory power. Although there are not large regional effects, the models change for different regions of the country.

scholarly journals PENERAPAN METODE PERMUKAAN RESPONS DALAM MASALAH OPTIMALISASI

2013 ◽  
Vol 2 (2) ◽  
pp. 32
Author(s):  
ADE KUSUMA DEWI ◽  
I WAYAN SUMARJAYA ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Orthogonal Polynomial ◽  
Optimal Level ◽  
The Other ◽  
Polynomial Method ◽  
Response Variable ◽  
Optimal Response ◽  
Independent Variables ◽  
Surface Method ◽  
Independent Variable ◽  
The Relationship

The experiments were conducted to determine the relationship between response variable and independent variable and the effect of independent variables to response variable. Multiple comparison tests can be used to find the level that makes optimal response. However, this test has a drawback that it only finds the optimal level tested at the level being considered. Thus test is more suitable for qualitative independent variables. On the other hand, for quantitative independent variables we can use the orthogonal polynomial method and response surface method (RSM).The purpose of this research is to apply RSM to produce optimal response. It can be concluded that RSM is an efficient used to find the level of independent variables to makes optimal response.

scholarly journals Scottish rehabilitation services: their relationship to socio-economic deprivation

1993 ◽  
Vol 17 (6) ◽  
pp. 339-340
Author(s):  
Robin G. McCreadie ◽  
Douglas J. Williamson
Keyword(s):  
Mentally Ill ◽  
Social Deprivation ◽  
Psychiatric Hospitals ◽  
Strong Relationship ◽  
Socioeconomic Deprivation ◽  
Community Resources ◽  
Psychiatric Admission ◽  
Admission Rates ◽  
Catchment Areas ◽  
The Relationship

It is well established that there is a strong relationship between psychiatric admission rates and socioeconomic deprivation; the more deprived the area, the more admissions may be expected (Hirsch, 1988). In the development of community resources for the mentally ill, therefore, an aim might be to site the majority of facilities in areas of greatest social deprivation, as that is where the majority of patients will live. It might also be expected that areas of greater deprivation would have more professional NHS staff. The present survey examines the siting of rehabilitation and support services in the catchment areas of Scottish psychiatric hospitals in relation to measures to socioeconomic deprivation. It also examines the relationship between deprivation and numbers of professional NHS staff in the different catchment areas.

scholarly journals PENGARUH PEMERIKSAAN PAJAK TERHADAP KEPATUHAN WAJIB PAJAK DAN DAMPAKNYA TERHADAP EFEKTIVITAS PENERIMAAN PAJAK PENGHASILAN BADAN

2018 ◽  
Vol 2 (2) ◽  
pp. 115-143
Author(s):  
Neng Siti RW ◽  
Agus Bagianto ◽  
Yuniati Yuniati
Keyword(s):  
Research Method ◽  
Employee Performance ◽  
The Other ◽  
Linear Regression Equation ◽  
Compensation Policy ◽  
Independent Variables ◽  
Descriptive Research ◽  
Is Research ◽  
Direct Compensation ◽  
The Relationship

Human resources are a supporting factor for companies to survive in competition. Compensation plays an important role in improving employee performance, one of the main reasons a person works is to make ends meet. Someone will work maximally to get the compensation in accordance with expectations. The compensation policy in addition to rewarding employees for the work performed by employees is also one way to retain potential employees. Based on the variables studied, the research method used in this research is descriptive and associative method. Descriptive research is a study conducted to determine the value of independent variables and does not make the comparison of variables with other variables Descriptive research here aims to obtain a picture of direct compensation, indirect compensation and employee performance at PT Pranata Jaya Abadi. While the method of associative research is research that aims to determine the influence or also the relationship between two variables or more. The results of this study show a multiple linear regression equation as follows: Y = 0.414 + 0.997X1 + 0.866X2, which can be interpreted as that the variables X1 and X2 are zero (0), then the variable Y will be worth 0.414 units; if the direct compensation (X1) increases by one unit and the other variable is constant, then the Y variable will increase by 0.997 units, and if the indirect compensation (X2) increases by one unit and the other variable is constant, then the Y variable will increase by 0.866 units. The conclusion of this study obtained the value of determination coefficient of 82.7% or the value of 0.827 which indicates the meaning that direct compensation (X1) and indirect compensation (X2) gives simultaneous effect of 82.7% on employee performance (Y ). While the rest of 17.3% influenced by other factors that ignored the author. The value of Adjusted R2 0.820 or the value of 82.0% indicating the meaning that, if there are other independent variables to be included, direct and indirect compensation variables, remain to have an effect of 82.0%. Against employee performance.

scholarly journals Oil Price Shocks and Stock Market Performance: A comparison between Oil Exporting and Oil Importing Nations

2021 ◽  
Vol 15 (2) ◽  
pp. 118-134
Author(s):  
Muhammad Farhan ◽  
◽  
Syed Shahid Zaheer Zaidi
Keyword(s):  
Stock Market ◽  
Oil Prices ◽  
Oil Price ◽  
The Other ◽  
Independent Variables ◽  
Stock Market Performance ◽  
The World ◽  
The Impact ◽  
Bound Test ◽  
The Relationship

The paper explores the impact of shocks in oil prices on the stock market for the oil importing and exporting nations. As Pakistan is heavily dependent on imports of oil therefore, we focus on Pakistan as an oil importing nation and have taken Iran, as an oil exporting nation because, it is considered to be among top ten nations of the world that exports oil. Various studies in Pakistan have investigates the relationship between shocks in prices of oil and return on the stock but none of the study has examined the association between shocks in oil prices and return on the stock market by comparing Pakistan and Iran as an oil importer and exporter nations of the world. This study has employed Autoregressive Distributed Lag model to find out the relationship between dependent and independent variables. We have taken prices of oil as an independent variable, whereas, stock price has been taken as a dependent variable. On the other hand, rate of exchange and rate of interest are the other independent variables. The results of this study and bound test reveals a long run association between prices of oil and the stock return for both nations. It has been indicated in the results that high oil prices have an adverse impact on market of stock for an oil importing nation (i.e., Pakistan) and have positively impacted on Iran which is an oil exporter nation. The results confirm that oil price shock contributed towards positively affecting the market of stock of an oil exporter nation but negatively affected the stock market if an oil importing nation. The author recommended the investors of both nations to evaluate various alternatives to diversify portfolios of their stock market by utilizing other financial assets.

scholarly journals PENGARUH KOMPENSASI LANGSUNG DAN KOMPENSASI TIDAK LANGSUNG TERHADAP KINERJA KARYAWAN BAGIAN STAFF OPERASIONAL PT PRANATA JAYA ABADI BANJARAN

2018 ◽  
Vol 2 (2) ◽  
pp. 90-114
Author(s):  
Wandy Zulkarnaen ◽  
Risa Herlina
Keyword(s):  
Research Method ◽  
Employee Performance ◽  
The Other ◽  
Linear Regression Equation ◽  
Compensation Policy ◽  
Independent Variables ◽  
Descriptive Research ◽  
Is Research ◽  
Direct Compensation ◽  
The Relationship

Human resources are a supporting factor for companies to survive in competition. Compensation plays an important role in improving employee performance, one of the main reasons a person works is to make ends meet. Someone will work maximally to get the compensation in accordance with expectations. The compensation policy in addition to rewarding employees for the work performed by employees is also one way to retain potential employees. Based on the variables studied, the research method used in this research is descriptive and associative method. Descriptive research is a study conducted to determine the value of independent variables and does not make the comparison of variables with other variables Descriptive research here aims to obtain a picture of direct compensation, indirect compensation and employee performance at PT Pranata Jaya Abadi. While the method of associative research is research that aims to determine the influence or also the relationship between two variables or more. The results of this study show a multiple linear regression equation as follows: Y = 0.414 + 0.997X1 + 0.866X2, which can be interpreted as that the variables X1 and X2 are zero (0), then the variable Y will be worth 0.414 units; if the direct compensation (X1) increases by one unit and the other variable is constant, then the Y variable will increase by 0.997 units, and if the indirect compensation (X2) increases by one unit and the other variable is constant, then the Y variable will increase by 0.866 units. The conclusion of this study obtained the value of determination coefficient of 82.7% or the value of 0.827 which indicates the meaning that direct compensation (X1) and indirect compensation (X2) gives simultaneous effect of 82.7% on employee performance (Y ). While the rest of 17.3% influenced by other factors that ignored the author. The value of Adjusted R2 0.820 or the value of 82.0% indicating the meaning that, if there are other independent variables to be included, direct and indirect compensation variables, remain to have an effect of 82.0%. Against employee performance.

scholarly journals Pengaruh CAR dan FDR Terhadap Pembiayaan Murabahah dengan NPF Sebagai Variabel Moderating

2021 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Evita Yulyani ◽  
Nana Diana
Keyword(s):  
Quantitative Study ◽  
Commercial Banks ◽  
Secondary Data ◽  
Financial Statements ◽  
The Other ◽  
Independent Variables ◽  
The Relationship

This study aims to know the effect of CAR and FDR variables on Murabahah financing partially and simultaneously, besides, this study also examined the influence of NPF variables in moderating the relationship between independent variables and Murabahah financing. This research is a quantitative study with a sample of 11 (eleven) Syariah Commercial Banks registered with the Otoritas Jaa Keuangan in 2015-2019 that meet the researchers' criteria. The data used in this study is secondary data in the form of financial statements obtained from the website of each bank that is a sample of research. The results showed that CAR had no effect and significant on Murabahah financing, FDR had no effect and significant on Murabahah financing, and also simultaneously CAR and FDR did not affect muarabah financing. On the other side, the NPF as moderating variable show that a map to the CAR on Murabahah financing,  the NPF moderating the FDR on Murabahah financing, and also the NPF moderating the influence of CAR and FDR on Murabahah financing simultaneously.

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