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Full-Text Articles in Applied Statistics
Jmasm 54: A Comparison Of Four Different Estimation Approaches For Prognostic Survival Oral Cancer Model, Wan Muhamad Amir, Muhammad Azeem, Masitah Hayati Harun, Zalila Ali, Mohamad Shafiq
Jmasm 54: A Comparison Of Four Different Estimation Approaches For Prognostic Survival Oral Cancer Model, Wan Muhamad Amir, Muhammad Azeem, Masitah Hayati Harun, Zalila Ali, Mohamad Shafiq
Journal of Modern Applied Statistical Methods
Four types of estimation approaches for prognostic survival oral cancer model building are considered via a SAS algorithm: Efron’s Method, Exact Method, Breslow’s Method, and Discrete Method. Each method is illustrated separately and compared according to their coefficient parameter. An approach is considered by adding a bootstrapping technique for each handling ties method and a complete SAS algorithm is supplied for each proposed method, including methods for handling ties.
Estimation Of Zero-Inflated Population Mean: A Bootstrapping Approach, Khyam Paneru, R. Noah Padgett, Hanfeng Chen
Estimation Of Zero-Inflated Population Mean: A Bootstrapping Approach, Khyam Paneru, R. Noah Padgett, Hanfeng Chen
Journal of Modern Applied Statistical Methods
A mixture model was adopted from the maximum pseudo-likelihood approach under complex sampling designs to estimate the mean of zero-inflated population. To overcome the complexity and assumptions of asymptotic distribution, the maximum pseudo-likelihood function was used, but a bootstrapping procedure was proposed as an alternative. Bootstrap confidence intervals consistently capture the true means of zero-inflated populations of the simulation studies.
Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya
Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya
Journal of Modern Applied Statistical Methods
The most important ingredient in Bayesian analysis is prior or prior distribution. A new prior determination method was developed under the framework of parametric empirical Bayes using bootstrap technique. By way of example, Bayesian estimations of the parameters of a normal distribution with unknown mean and unknown variance conditions were considered, as well as its application in comparing the means of two independent normal samples with several scenarios. A Monte Carlo study was conducted to illustrate the proposed procedure in estimation and hypothesis testing. Results from Monte Carlo studies showed that the bootstrap prior proposed is more efficient than the …
Bootstrapping Confidence Intervals For Robust Measures Of Association, Jason E. King
Bootstrapping Confidence Intervals For Robust Measures Of Association, Jason E. King
Journal of Modern Applied Statistical Methods
A Monte Carlo simulation study compared four bootstrapping procedures in generating confidence intervals for the robust Winsorized and percentage bend correlations. Results revealed the superior resiliency of the robust correlations over r, with neither outperforming the other. Unexpectedly, the bootstrapping procedures achieved roughly equivalent outcomes for each correlation.
Exact Level And Power Of Permutation, Bootstrap, And Asymptotic Tests Of Trend, Christopher D. Corcoran, Cyrus R. Mehta
Exact Level And Power Of Permutation, Bootstrap, And Asymptotic Tests Of Trend, Christopher D. Corcoran, Cyrus R. Mehta
Journal of Modern Applied Statistical Methods
We develop computational tools that can evaluate the exact size and power of three tests of trend (e.g., permutation, bootstrap and asymptotic) without resorting to large-sample theory or simulations. We then use these tools to compare the operating characteristics of the three tests. It is seen that the bootstrap test is ultra-conservative relative to the other two tests and as a result suffers from a severe deterioration in power. The power of the asymptotic test is uniformly larger than that of the other two tests, but it fails to preserve the Type I error for most of the range of …