Landaburu Jiménez, María ElenaMorales González, DomingoPardo Llorente, Leandro2023-06-202023-06-202005-070932-502610.1007/BF02762841https://hdl.handle.net/20.500.14352/50109The well-known chi-squared goodness-of-fit test for a multinomial distribution is generally biased when the observations are subject to misclassification. In Pardo and Zografos (2000) the problem was considered using a double sampling scheme and phi-divergence test statistics. A new problem appears if the null hypothesis is not simple because it is necessary to give estimators for the unknown parameters. In this paper the minimum phi-divergence estimators are considered and some of their properties are established. The proposed phi-divergence test statistics are obtained by calculating phi-divergences between probability density functions and by replacing parameters by their minimum phi-divergence estimators in the derived expressions. Asymptotic distributions of the new test statistics are also obtained. The testing procedure is illustrated with an exampleengjournal articlehttp://www.springerlink.com/content/j151063g0r87lg10/fulltext.pdfhttp://www.springerlink.com/restricted access519.24MisclassificationDouble samplingDivergence estimatorsGoodness-of-fit testsDivergence statisticsMuestreo (Estadística)1209.10 Teoría y Técnicas de Muestreo