Prediction of tumour pathological subtype from genomic profile using sparse logistic regression with random effects

The purpose of this study is to highlight the application of sparse logistic regression models in dealing with prediction of tumour pathological subtypes based on lung cancer patients'' genomic information. We consider sparse logistic regression models to deal with the high dimensionality and correlation between genomic regions. In a hierarchical likelihood (HL) method, it is assumed that the random effects follow a normal distribution and its variance is assumed to follow a gamma distribution. This formulation considers ridge and lasso penalties as special cases. We extend the HL penalty to include a ridge penalty (called ‘HLnet’) in a similar principle of the elastic net penalty, which is constructed from lasso penalty. The results indicate that the HL penalty creates more sparse estimates than lasso penalty with comparable prediction performance, while HLnet and elastic net penalties have the best prediction performance in real data. We illustrate the methods in a lung cancer study.     

Women who sacrifice themselves for everybody: qualitative research with mothers of disabled children

This study, from a feminist perspective, aimed at examining the experiences of women whose children with cerebral palsy received a treatment at a physiotherapy and rehabilitation center located in Ankara, Turkey. The study intended to reveal the perceptions of in-family roles of women with disabled children, their participation in public life, and their self-concept within the scope of feminist social work. Thus, the objective of the present study was to contribute to the understanding of the fact that non gender-blind services should be developed in this field on the basis of social justice and human rights, which constitutes the fundamental philosophy of social work. Qualitative research method was employed in the study where data were analyzed through content analysis. The findings of the study were interpreted under four main themes: the lives of the women with disabled children after their disabled children were born; being a woman within the scope of family life, participation in decision-making processes, and domestic division of labor; participation in public life and relations with women's associations; the self-sacrifice; and the suggestions of women concerning self-realization within the scope of self-concept.     

Contingencies versus External Pressure: Professionalization in Boards of Firms Affiliated to Family Business Groups in Late‐Industrializing Countries

We examine the antecedents of professionalization in boards of firms affiliated to family business groups, increasingly recognized in the literature as the dominant form of big business organization in many late‐industrializing countries. Dimensions of board professionalization that we include in our study are board size, ratio of salaried executives and outsider presence. We compare predictions on board composition derived from contingency, institutional and power perspectives. Turkish family business groups, considered as an archetypal example of this form of organization, provide the empirical setting for the study, with data on 299 firms affiliated to ten different family business groups. Our results provide greater support for institutional and power perspectives, showing that, relative to internal and external complexity facing affiliate firms, institutional pressures and the presence of joint venture partners better predict board professionalization.     

Does Perceived Social Support Buffer the Negative Effects of Type C Personality on Quality of Life of Breast Cancer Patients?

The present study investigated possible Type C personality–quality of life (QOL) relationship, and the moderating role of perceived social support in this relation among 101 postoperative breast cancer patients. Participants were from different cities in Turkey but receiving treatment in the capital, Ankara. Obtained data were analyzed by moderated regression analysis. According to the results, Type C personality was not related to the QOL of participants, however, higher perceived social support was associated with better QOL in patients. Also, perceived social support moderated Type C personality–QOL relation. Accordingly, patients high on Type C personality and perceived social support had the highest QOL. In contrast, patients high on Type C personality and low on perceived social support had the lowest QOL. Findings, as well as the strengths and limitations of the study, were discussed in the light of the relevant literature. As a possible clinical implication, enhancement of social support networks of the patients were suggested.     

Clustering the mixed panel dataset using Gower's distance and k-prototypes algorithms

ABSTRACT

Panel datasets have been increasingly used in economics to analyze complex economic phenomena. Panel data is a two-dimensional array that combines cross-sectional and time series data. Through constructing a panel data matrix, the clustering method is applied to panel data analysis. This method solves the heterogeneity question of the dependent variable, which belongs to panel data, before the analysis. Clustering is a widely used statistical tool in determining subsets in a given dataset. In this article, we present that the mixed panel dataset is clustered by agglomerative hierarchical algorithms based on Gower's distance and by k-prototypes. The performance of these algorithms has been studied on panel data with mixed numerical and categorical features. The effectiveness of these algorithms is compared by using cluster accuracy. An experimental analysis is illustrated on a real dataset using Stata and R package software.     

Countervailing institutional forces: corporate governance in Turkish family business groups

This longitudinal study investigates the impact of national and international pressures to improve corporate governance in an emerging economy from an institutional theory perspective. Recently, family business groups (FBGs), the dominant form of organizing in emerging economies, have been criticized by policy makers for their poor governance structures. A common recommendation to FBGs has been increasing the number of independent, outsider directors on their boards. Thus, change in the board compositions of the quoted subsidiaries of the six biggest FBGs is analyzed over 2002–2006. One-way-ANOVA and t-tests were used as statistical tools. Findings reveal that there has not been a statistically significant change in board compositions over the research period. FBGs were found to resist institutional pressures through ‘avoidance’, ‘defiance’ and “manipulation” strategies due to the absence of coercive pressures and multiple forms of ‘institutional work’ for change.     

Improving Humanitarian Operations through Technology‐Enabled Collaboration

Humanitarian supply chains involve many different entities, such as government, military, private, and non‐governmental organizations and individuals. Well‐coordinated interactions between entities can lead to synergies and improved humanitarian outcomes. Information technology (IT) tools can help facilitate collaboration, but cost and other barriers have limited their use. We document the use of an IT tool to improve last‐mile supply distribution and data management in one of many camps for internally displaced persons after the January 2010 earthquake in Haiti, and we describe other current uses of technology in camp management. Motivated by these examples and the interest among humanitarian organizations in expanding the use of such tools to facilitate coordination, we introduce a cooperative game theory model and explore insights about the conditions under which multi‐agency coordination is feasible and desirable. We also outline an agenda for future research in the area of technology‐enabled collaboration in the humanitarian sector.     

Factors effecting the model performance measures area under the ROC curve,net reclassification improvement and integrated discrimination improvement

ABSTRACT

The aim of this study is to investigate the impact of correlation structure, prevalence and effect size on the risk prediction model by using the change in the area under the receiver operating characteristic curve (ΔAUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). In simulation study, the dataset is generated under different correlation structures, prevalences and effect sizes. We verify the simulation results with the real-data application. In conclusion, the correlation structure between the variables should be taken into account while composing a multivariable model. Negative correlation structure between independent variables is more beneficial while constructing a model.     

Thirteen‐ and 18‐month‐old Infants Recognize When They Need Referential Information

To learn from conspecifics, infants would be greatly advantaged by knowing when to seek information from them. Although in prior work infants used a labeler's gaze direction to infer the referent of a novel label, it was unclear whether infants in these studies recognized that they needed information or were happening upon the information by simply orienting to the labeler's voice. To address this issue, we presented 13‐ and 18‐month‐olds with either one or two novel objects and provided a novel label. If infants seek referential information, they should look more to the labeler in the presence of two objects relative to one object, because the labeler's intended referent is highly ambiguous in the two‐object case. This prediction was confirmed in two studies. In contrast, infants' looking was equivalent in the presence of one vs. two objects in a baseline phase, when no labels were provided. Thus, 13‐ and 18‐month‐olds actively seek clarifying gaze information to resolve ambiguous learning situations. Word learning appears to be a rich pragmatic process as early as the end of the first year of life.     

Race and Redistricting: What the Print Media Conveys to the Public about the Role of Race

In a series of voting rights cases, the U.S. Supreme Court held that race-based redistricting, particularly the intentional formation of majority–minority districts (districts in which voters of color constitute a majority of eligible voters) may be unconstitutional if race was the predominant factor in the formation of the district. The Court stated that "redistricting legislation that is so bizarre on its face that it is unexplainable on grounds other than race" may violate the Constitution because of the messages such districts send to the public ( Shaw v. Reno , 1993 ). Yet neither the Court nor social scientists have examined whether the existence of race-conscious majority–minority districts sends messages to voters and what the nature of these messages may be. This research begins to address this scientific issue. In a quantitative content analysis, we examined messages about racial redistricting conveyed to citizens via the print media. Our sample consisted of 355 newspaper articles about redistricting included in the Lexis–Nexis database between 1990 and 2005. We found that newspaper coverage of racial districting contains messages to citizens about the motives involved in redistricting, the individuals and groups who are responsible for it, and its actual and expected effects. This finding is consistent with the Supreme Court's assumption that districts, particularly bizarrely shaped ones, convey distinct messages to voters. The specific messages communicated varied in important ways across the articles. Newspapers in states subject to Section 5 of the Voting Rights Act because of their history of discrimination against voters of color covered racial redistricting differently than states not subject to Section 5. We discuss the legal and theoretical implications of these findings for understanding the role of race in legislative redistricting efforts.