Nonparametric Analysis of Longitudinal Binary Data: An Application to the Intergroup Prisoner's Dilemma Game

The intergroup prisoner's dilemma game was suggested by Bornstein (1992, Journal of Personality and Social Psychology. 7, 597–606) for modelling intergroup conflicts over continuous public goods. We analyse data of an experiment in which the game was played for 150 rounds, under three matching conditions. The objective is to study differences in the investment patterns of players in the different groups. A repeated measures analysis was conducted by Goren and Bornstein (1999, Games and Human Behaviour: Essays in Honor of Amnon Rapoport, pp. 299–314), involving data aggregation and strong distributional assumptions. Here we introduce a nonparametric approach based on permutation tests. Two new measures, the cumulative investment and the normalised cumulative investment, provide additional insight into the differences between groups. The proposed tests are based on the area under the investment curves. They identify an overall difference between the groups as well as pairwise differences. A simultaneous confidence band for the mean difference curve is used to detect the games which account for any pairwise difference. Copyright Kluwer Academic Publishers 2003randomisation tests, multiple comparisons, displacement approach, conflict resolution problems,

Venous Thromboembolism and Its Risk Factors in Children with Acute Lymphoblastic Leukemia in Israel: A Population-Based Study

Venous thromboembolism (VTE) is a serious complication of acute lymphoblastic leukemia (ALL) therapy. The aim of this population-based study was to evaluate the rate, risk factors, and long-term sequelae of VTE in children treated for ALL. The cohort included 1191 children aged 1–19 years diagnosed with ALL between 2003–2018, prospectively enrolled in two consecutive protocols: ALL-IC BFM 2002 and AIEOP-BFM ALL 2009. VTEs occurred in 89 patients (7.5%). Long-term sequelae were uncommon. By univariate analysis, we identified four significant risk factors for VTEs: Severe hypertriglyceridemia (p = 0.005), inherited thrombophilia (p < 0.001), age >10 years (p = 0.015), and high-risk ALL group (p = 0.039). In addition, the incidence of VTE was significantly higher in patients enrolled in AIEOP-BFM ALL 2009 than in those enrolled in ALL-IC BFM 2002 (p = 0.001). Severe VTE occurred in 24 children (2%), all of whom had at least one risk factor. Elevated triglyceride levels at diagnosis did not predict hypertriglyceridemia during therapy. In a multivariate analysis of 388 children, severe hypertriglyceridemia and inherited thrombophilia were independent risk factors for VTE. Routine evaluation for these risk factors in children treated for ALL may help identify candidates for intervention

Ethnic variation in medical and lifestyle risk factors for B cell non-Hodgkin lymphoma: A case-control study among Israelis and Palestinians

<div><p>Background</p><p>Risk factors for B-cell non-Hodgkin lymphoma (B-NHL) have not been assessed among Palestinian Arabs (PA) and Israeli Jews (IJ).</p><p>Methods</p><p>In a case-control study we investigated self-reported medical and lifestyle exposures, reporting odds ratios (ORs) and 95% confidence intervals [CIs], by ethnicity, for overall B-NHL and subtypes.</p><p>Results</p><p>We recruited 823 cases and 808 healthy controls. Among 307 PA/516 IJ B-NHL cases (mean age at diagnosis = 51 [±17] versus 60 [±15] years, respectively) subtype distributions differed, with diffuse large B-cell lymphoma (DLBCL) being prominent among PA (71%) compared to IJ (41%); follicular lymphoma (FL), was observed in 14% versus 28%, and marginal zone lymphoma, in 2% versus 14%, respectively. Overall B-NHL in both populations was associated with recreational sun exposure OR = 1.43 [CI:1.07–1.91], black hair-dye use OR = 1.70 [CI:1.00–2.87], hospitalization for infection OR = 1.68 [CI:1.34–2.11], and first-degree relative with hematopoietic cancer, OR = 1.69 [CI:1.16–2.48]. An inverse association was noted with alcohol use, OR = 0.46 [CI:0.34–0.62]. Subtype-specific exposures included smoking (FL, OR = 1.46 [CI:1.01–2.11]) and >monthly indoor pesticide use (DLBCL, OR = 2.01 [CI:1.35–3.00]). Associations observed for overall B-NHL in PA only included: gardening OR = 1.93 [CI:1.39–2.70]; history of herpes, mononucleosis, rubella, blood transfusion (OR>2.5, P<0.01 for all); while for IJ risk factors included growing fruits and vegetables, OR = 1.87 [CI:1.11–3.15]; and self-reported autoimmune diseases, OR = 1.99 [CI:1.34–2.95].</p><p>Conclusions</p><p>In these geographically proximate populations we found some unique risk factors for B-NHL. Heterogeneity in the observed associations by ethnicity could reflect differences in lifestyle, medical systems, and reporting patterns, while variations by histology infer specific etiologic factors for lymphoma subtypes.</p></div

Life style exposures- Adjusted OR for B-NHL and subtypes, overall and by population^□.

<p>Lists the overall odds ratio (OR) with 95% confidence interval (CI) for all risk factors affecting overall B-cell non-Hodgkin lymphoma (B-NHL) and subtypes: diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL) and marginal zone lymphoma (MZL), stratified by population (Jews, Arabs), frequency matched by sex and age categories (4 year groupings); adjusted for marital status, education (yrs), ethnic origin for Jews (Ashkenazi, North African, West Asian and Sephardic) and residential region for Arabs (North, South, Center, other). The columns list the exposure category and the OR. The colored grid indicates the OR associated with the exposure for each subtype separately. Red (blue) represents the exposure increases (decreases) risk. ^Xindicates an association with P<0.05, whereas ^XXindicates P<0.01. <i>m</i> indicates missing due to lack of data. <i>Int</i> indicates interaction between exposure and sub-populations P<0.05. ^□based on schema designed by Morton et al.</p

B-cell non-Hodgkin lymphoma (B-NHL) subtype distribution by population.

<p>B-cell non-Hodgkin lymphoma (B-NHL) subtype distribution by population.</p

Demographic characteristics for Israeli Jews and Palestinian Arabs by case-control status for overall B-cell non-Hodgkin lymphoma.

<p>Demographic characteristics for Israeli Jews and Palestinian Arabs by case-control status for overall B-cell non-Hodgkin lymphoma.</p