Two approaches are used to assess the distribution assumptions. One is by implementing numerically convoluted, theoretical Goodness of Fit (GoF) tests such as the Chi Square, Anderson Darling or Kolmogorov-Smirnov. Their lengthy calculations often require the use of specialized software, not always readily available. On the other hand, there exist practical procedures that are easy to understan...

In the common nonparametric regression model the problem of testing for a specific parametric form of the variance function is considered. Recently Dette and Hetzler (2008) proposed a test statistic, which is based on an empirical process of pseudo residuals. The process converges weakly to a Gaussian process with a complicated covariance kernel depending on the data generating process. In the ...

We propose non-nested hypotheses tests for conditional moment restriction models based on the method of generalized empirical likelihood (GEL). By utilizing the implied GEL probabilities from a sequence of unconditional moment restrictions that contains equivalent information of the conditional moment restrictions, we construct Kolmogorov-Smirnov and Cramér-von Mises type moment encompassing te...

This paper derives asymptotic power functions for Cramer-von Mises (CvM) style tests for inference on a finite dimensional parameter defined by conditional moment inequalities in the case where the parameter is set identified. Combined with power results for Kolmogorov-Smirnov (KS) tests, these results can be used to choose the optimal test statistic, weighting function and, for tests based on ...

Methods The study included data from out-patient medical record on 69 JIA patients (45 children, 24 adults) who received ETN therapy during 2004 till 2010. Treatment efficacy was assessed using the ACR (American College of Rheumatology) Pedi 30, 50 and 70 response. Therapy was evaluated after 3, 6, 12 and 24 months (mo) of ETN treatment. Safety was assessed by recording ETN adverse events (AE)....

This study makes an innovative approach, since it applies a set of diversified tests, which have not been used on a joint basis until now, in order to study the contagion effects of financial crises in the stock markets of developed countries. This is particularly important due to the fact that existing literature has so far failed to adequately address the effects of financial crisis on the st...

In this paper we discuss goodness of fit tests for the distribution of technical inefficiency in stochastic frontier models. If we maintain the hypothesis that the assumed normal distribution for statistical noise is correct, the assumed distribution for technical inefficiency is testable. We show that a goodness of fit test can be based on the distribution of estimated technical efficiency, or...

Using a stochastic dominance approach in an international dataset of about 10,000 Catholic subjects, we show that incentives (based on absolute belief) play a crucial role in religious practice (church attendance and prayer). Furthermore, we find that when both positive (heaven) and negative (hell) incentives are available, the former have a much stronger effect than the latter. The results are...

Goodness-of-fit tests gauge whether a given set of observations is consistent (up to expected random fluctuations) with arising as independent and identically distributed (i.i.d.) draws from a user-specified probability distribution known as the “model.” The standard gauges involve the discrepancy between the model and the empirical distribution of the observed draws. Some measures of discrepan...

The Kolmogorov-Smirnov test determines the consistency of empirical data with a particular probability distribution. Often, parameters in the distribution are unknown, and have to be estimated from the data. In this case, the Kolmogorov-Smirnov test depends on the form of the particular probability distribution under consideration, even when the estimated parameter-values are used within the di...