Multilevel Augmented Pairs Second-Order Response Surface Designs and Their Robustness to Missing Data

Missing observations can occur even in a well-planned experiment. The effect of missing observations can be much more serious when the design is saturated or near saturated. The levels of factor settings that make a design more robust to missing observations are of great importance in the sense that the loss for missing observations becomes minimum. In this study, new augmented pairs minimax loss designs are constructed, which are more robust to one missing design point than the augmented pairs designs presented by Morris (2000 Morris , M. D. ( 2000 ). A class of three-level experimental designs for response surface modeling . Technometrics 42 : 111 – 121 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). New designs are compared with augmented pairs designs, central composite designs, and small composite designs under generalized scaled standard deviations. The model used is also studied for the regression coefficient estimates.     

Can 18‐Month‐Old Infants Learn Words by Listening In on Conversations?

Previous research has shown that children as young as 2 can learn words from 3rd‐party conversations (Akhtar, Jipson, & Callanan, 2001). The focus of this study was to determine whether younger infants could learn a new word through overhearing. Novel object labels were introduced to 18‐month‐old infants in 1 of 2 conditions: directly by an experimenter or in the context of overhearing the experimenter use the word while interacting with another adult. The findings suggest that, when memory demands are not too high, 18‐month‐old infants can learn words through overhearing.     

Implications of selected production planning functions: Impact analysis through simulation

When capacity differences are minimized through an efficient algorithm, and integration of capacity planning with any production planning system is performed, it affects some elements of production planning functions. In the reverse way, some elements of production planning and management techniques also affect the effectiveness of capacity planning. These happen because capacity planning processes, production planning processes and production management techniques are not standalone sub-systems, rather these are totally dependent on each other. This paper aims at determining and formulating the effects of some of the selected elements of capacity and production planning functions on each other. This study is conducted using simulation in object-oriented SIMPLE+ + system.     

Determinants of Profitability of Banking Sector in India

India currently is one of the fastest growing economies in the world. One sector of Indian economy that has played a critical role in transforming the Indian economy has been its banking sector. But this sector of Indian economy has also gone through a major transition that is still in progress. Many events and policies have contributed in this transition. One pivotal variable has been the growing profitability of this sector in the recent years. But profitability in banking sector is affected by numerous factors. These factors can be internal or external. In this research we shall try to examine the most important factors that may stem from both internal and external factors, which affect profitability of Indian banking sector. For this study a balanced panel data set is used that is drawn from Indian banking industry. The data is compiled for the purpose of investigating the nature of the relationship between the profitability and the factors that determine profitability of banks in India. The results of the study clearly demonstrate a close correlation between both internal and external factors and the level of profitability of banks in India.     

Construction of Balanced Incomplete Block Designs Using Cyclic Shifts

Balanced incomplete block designs (BIBDs) play important role in design of experiments, especially in field experiments. These designs ensure that treatments are compared with equal precision. Several methods are available in the literature to construct BIBDs but in this article some infinite series of these designs are presented by method of cyclic shifts. This method expresses some standard properties of a design just through examining the sets of shifts rather than studying the whole design.     

Some Classes of Binary Block Neighbor Designs

Neighbor designs are useful to neutralize the neighbor effects. In this paper two classes of these designs are constructed in circular binary blocks of size 4, 8, …, 24. First class consists of six infinite series of nearest neighbor designs in which each pair of distinct treatments appears once as neighbors. Second class also deals with six infinite series of these designs in which each pair of distinct treatments appears twice as neighbors. A catalog of nearest neighbor designs is also compiled in circular binary blocks for odd number of treatments from 23 to 99.     

Universally Optimal Designs Balanced for Neighbor Effects

The performance of a treatment is affected by the treatments applied to its adjacent plots, especially in the experiments of agriculture, horticulture, forestry, serology and industry. Neighbor designs ensure that treatment comparisons are least affected by neighbor effects, therefore, this is a rich field of investigation. In this paper, criterion for construction of universally optimal neighbor balanced designs is discussed.     

Augmented Box-Behnken Designs for Fitting Third-Order Response Surfaces

Box-Behnken designs are popular with experimenters who wish to estimate a second-order model, due to their having three levels, their simplicity and their high efficiency for the second-order model. However, there are situations in which the model is inadequate due to lack of fit caused by higher-order terms. These designs have little ability to estimate third-order terms. Using combinations of factorial points, axial points, and complementary design points, we augment these designs and develop catalogues of third-order designs for 3–12 factors. These augmented designs can be used to estimate the parameters of a third-order response surface model. Since the aim is to make the most of a situation in which the experiment was designed for an inadequate model, the designs are clearly suboptimal and not rotatable for the third-order model, but can still provide useful information.