No abstract available.

No abstract available.

A multiple regression analysis using ordinary least square (OLS) is frequently used for the projection of healt expenditure as well as for the identification of factors affecting health care costs. Data for the analysis often have mixed characteristics of time series and cross section. Parameters as a result of OLS estimation, in this case, are no longer the best linear unbiased estimators (BLUE) because the data do not satisfy basic assumptions of regression analysis. The study theoretically examined statistical problems induced when OLS estimation was applied with the time series cross section data. Then both the OLS regression and time series cross section regression (TSCS regression) were applied to the same empirical data. Finally, the difference in parameters between the two estimations were explained through residual analysis.
Health Care Costs ; Health Expenditures*

Ecologic studies are widely used in all fields of public health on account of accesibility of data. However, two problems related to these studies have been brought up. The first is ecological fallacy occurred in the course of interpreting the ecologic level of exposure-disease associations into individual level. The second is exposure isclassification which leads to serious bias. Nevertheless there is few methodologic study dealing joint effects of the two problems in ecologic study. This study was conducted to suggest an ecologic model not having an ecologic fallacy due to model linkage failure and a methodology for correcting the misclassification bias due to exposure-confounder misclassification. Finally, we suggest a criteria for the ecologic model selection. Main results are as follows: 1. A linear ecologic regression model has a serious ecological fallacy due to model linkage failure and the misclassification bias due to the exposure-confounder misclassification. 2. An interaction ecologic regression model has no ecological fallacy due to model linkage failure, but it is affected seriously by the exposure misclassification. However misclassification bias could be removed mathematically if the information related to the misclassification was known. 3. A log-linear ecologic regression model has an ecological fallacy due to model linkage failure. It is seriously biased as the individual risk ratio are increased, but relatively less affected by the exposure misclassification than interaction ecologic regression model. 4. One of the two ecologic regression model-interaction ecologic regression model and log-linear ecologic regression model- would be selected according to the information of individual risk ratio and exposure misclassification. But using a linear ecologic regression model should be avoided in any circumstance. The above results are only valid in case that there is no other source of ecological fallacy except model linkage failure. Also exposure and confounder are independent each other, measured binary, and having nondifferential misclassification. Since the above assumptions are somewhat strong in considering the real situations of ecologic studies, it is necessary to extend the scope of this study.
Bias (Epidemiology) ; Joints ; Odds Ratio ; Public Health

There are many epidemiologic studies to find the relationship between disease occurrence and categorized exposure variables which are measured in continuous scales. Recently, it has been found that the differential misclassification can arise when exposure variables are observed with measurement errors and categorized for the analysis. Even though the differential misclassification leads to serious misclassification bias, there is no theoretical attempt to correct the misclassification bias occuring in these circumstances. In this paper, we propose a new statistical method to reduce the misclassification bias due to dichotomizing continuous exposure variables. Since the exposure values are more likely to be misclassified when the true exposure values are close to the cutoff point, the method proposed here gives smaller weights in these case and more weights when these values are far from cutoff point. Simulation studies are performed to compare the bias and the power of the proposed method compared to other methods. Main results are as follows: 1. The proposed method produces the smaller bias and the higher power than the simple method which modifies misclassified data using sensitivity and specificity of exposure misclassification. 2. When the standard deviation of the measurement error are moderately large, the bias and the power of the proposed estimate are somewhat better than those of the modified estimate which excluding the misclassified observations in the analysis. In conclusion, the method proposed here is found to be useful in epidemiologic studies when continuous exposure variables are obtained with measurement error and categorized in the analysis.
Bias (Epidemiology) ; Sensitivity and Specificity ; Weights and Measures

The united states adopted DRG based prospective payment system (PPS) in order to control the inflation of health care costs. No study used statistical test while many studies reported the cost containing effect of the PPS. To study impacts of the PPS on the Medicare expenditure, this study set the following three hypotheses: (l) The PPS decelerated the increase in the hospital expenditure (part A), (2) the PPS accelerated the increase in the expenditure of outpatients and physicians (part B), (3) the increase in total expenditure was decelerated inspite of the spill over (substitution) effect because saving in the part A expenditure were greater than losses in the part B expenditure. The dependent variables are per capita hospital expenditure, per capita part B expenditure, and per capita total expenditure for the Medicare beneficiaries. An intervention analysis, which added intervention effect to the time series variation on the Box-Jenkins model, was used. The observations included 120 months from 1978 to 1987. The results are as follows: (l) The annual increase in the per capita part A expenditure was $5.11 after the implementation of DRG where as that before the PPS had been $11.1. The effect of the reduction ($5.99) was statistically significant (t=-3.9). (2) The spill over (substitution) effect existed because the annual increase in the per capita part B expenditure was accelerated by $l.73 (t=l.91) after the implementation of the PPS. (3) The increase in the total Medicine expenditure per capita was reduced by $4.26(t=-2.19) because the spill over effect was less than cost savings in the Part A expenditure.
Cost Savings ; Diagnosis-Related Groups* ; Health Care Costs ; Health Expenditures* ; Humans ; Inflation, Economic ; Medicare* ; Outpatients ; Prospective Payment System* ; United States

This study was conducted to find out an appropriate means for preventing the juvenile delinquency (JD), which is supposed to be greatly realted to family environment. The data were collected through a questionnaire survey with a means of writing by themself, to 257 middle and high school students and 309 juvenile delinquents who were in confinement. The questionnaire was consisted of 27 items of juvenile delinquencies, 15 questions about personal environment in their period of childhood, 36 questions on their home atmosphere, 25 items with regard to their parental behavior to their children in the rearing of them. The extent of delinquency was calculated by summing the numbers of experienced delinquencies of the listed items. The study subjects were divided into two groups; student group (SG) and juvenile delinquent group (JDG) and the collected data were analyzed with the extent of delinquency in each group by SPSS/PC+statistical package. The extent of JD was increased as the study subjects grew older, defective families were more common, total family income was more poor, parents' educational level was lower, personal expenses were higher and the conflicts between parents were more high in JDG as compared with of SG. The differences were statistically significant. As long as the extent of delinquency is concerned, delimquent points of JDG were significantly higher as compared with that of SG in all items except one item, below the primary school item in fathers' educational level. (In order to prevent JD in our country, it is recommended that educational level and the living standared of the lower class people should be raised, the sound families which do have less conflictsshould be established as much as possible, the present educational system which is making much conflicts between parents and their offsprings should be changed so that their given temperament would be brought up to the highest level, defective families should be reduced as much as possible and adults should not do actions that are considered not to be done by youngsters and must set a good example.)
Adult ; Atmosphere ; Child ; Humans ; Juvenile Delinquency* ; Parents ; Surveys and Questionnaires ; Temperament ; Writing

The purpose of this study was to determine the relationships among the health concern, health practice and health status of Koreans. This study utilized the data from Korean individuals(1,304 male and 1,495 females), whose ages were between 20 and 59. The data were analyzed using SAS version 6.04 and LISREL version 7.13. The analytic methods for the study were chi-square analysis and covariance structural analysis. The results of the study were as follows. (1) There were significant positive relationships between health concern level and health practice index, and between health practice index and self-perceived health status. (2)There were negative relationships between practice index and chronic illness, and between health practice index and acute illness only in female. (3) Based on the findings, the structural model of the health concern, health practice, health status and socioeconomic variables was established and then the covariance structural analysis was used. The higher educational level and economic status were, the higher the health concern was. And urban residents were much more concerned with their health than rural residents. The more persons were concerned with health, the more they did health practices. And the more the health practice was, the higher the health status was. The younger the persons were and the higher the health status of one's family was, the higher the health status was. In female, the higher the economic status was, the higher the health status was.
Chronic Disease ; Female ; Health Promotion ; Humans ; Male ; Models, Structural*

Missing data such as appropriateness ratings in clinical research are a common problem and this often yields a biased result. This paper aims to introduce the multiple imputation method to handle missing data in clinical research and to suggest that the multiple imputation technique can give more accurate estimates than those of a complete-case analysis. The idea of multiple imputation is that each missing value is replaced with more than one plausible value. The appropriateness method was developed as a pragmatic solution to problem of trying to assess "appropriate" surgical and medical procedures for patients. Cataract surgery was selected as one of four procedures that were evaluated as a part of the Clinical Appropriateness Initiative. We created mild to high missing rates of 10%, 30% and 50% and compared the performance of logistic regression in cataract surgery. We treated the coefficients in the original data as true parameters and compared them with the other results. In the mild missing rate (10%), the deviation from the true coefficients was quite small and ignorable. After removing the missing data, the complete-case analysis did not reveal any serious bias. However, as the missing rate increased, the bias was not ignorable and it distorted the result. This simulation study suggests that a multiple imputation technique can give more accurate estimates than those of a complete-case analysis, especially for moderate to high missing rates (30 - 50%). In addition, the multiple imputation technique yields better accuracy than a single imputation technique. Therefore, multiple imputation is useful and efficient for a situation in clinical research where there is large amounts of missing data.
Cataract Extraction/*methods ; Humans ; Logistic Models ; Research Support, Non-U.S. Gov't

No abstract available.