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• Application of time series in medical research

  14-22

  Mária Fazekasné Kis

  Views:

  65

  This article reviews the mortality data of chronic liver disease and cirrhosis, as well as tracheal, bronchial and lung cancers, in Hungary by methods of time series analysis. The methods of time series of death rates of chronic liver disease and cirrhosis as well as tracheal, bronchial and lung cancers and their reliability, are analysed from data available from WHO. The author used ARIMA models (autoregressive and integrated moving average models) and auto- and cross-correlation functions to study the substantial role an exogenous environmental factor has on incidences of
  death. The confidence intervals of autoregressive (AR) coefficient are compared to the standard normal distribution, the estimation of White’s theory and the continuous time estimation model.
  On the basis of the analysis, it may be concluded that chronic liver disease and cirrhosis can be influenced by an exogenous environmental factor, however, this relation cannot be demonstrated for deaths due to tracheal, bronchial or lung cancers. In each case, the continuous estimation of the AR(1) coefficients give the best results.
  The paper demonstrates how the presented methods can be applied to agricultural science.

• ROC analízis alkalmazása

  4-7

  Mária Fazekasné Kis

  Views:

  117

  According to publishings in foreign scientific journals, ROC (Receiver Operating Characteristic) analysis is a widely used method for analysing the diagnostic utility of clinical laboratory tests. In this paper, we explain the basic principles of ROC analysis and produce ROC curves, as well as demonstrate some ROC curves, which represent the results of diagnostic tests.