Ottar Hellevik

Bio: Ottar Hellevik is an academic researcher from University of Oslo. The author has contributed to research in topics: Social inequality & Happiness. The author has an hindex of 12, co-authored 33 publications receiving 842 citations.

Linear versus logistic regression when the dependent variable is a dichotomy

Abstract: The article argues against the popular belief that linear regression should not be used when the dependent variable is a dichotomy. The relevance of the statistical arguments against linear analyses, that the tests of significance are inappropriate and that one risk getting meaningless results, are disputed. Violating the homoscedasticity assumption seems to be of little practical importance, as an empirical comparison of results shows nearly identical outcomes for the two kinds of significance tests. When linear analysis of dichotomous dependent variables is seen as acceptable, there in many situations exist compelling arguments of a substantive nature for preferring this approach to logistic regression. Of special importance is the intuitive meaningfulness of the linear measures as differences in probabilities, and their applicability in causal (path) analysis, in contrast to the logistic measures.

Economy, values and happiness in norway ∗

Abstract: Why has the level of happiness in the Norwegian population not risen in parallel with the substantial increases in income and possessions in the period 1985-2001? An answer is sought by analysing data from a series of large representative surveys of the Norwegian population. Individual level correlations between indicators of health or family situation and happiness indicate that the measure of happiness is valid, and that happiness is not fully determined by personality traits, but affected also by changes in the circumstances of an individual. Several aspects of a person's economic situation turn out to have significant effects on happiness, in particular how the situation is subjectively experienced. Even if the development for some of these subjective indicators does not reflect the improve- ment in objective economic conditions, there is sufficient positive change to expect an increase in the level of happiness. The stability in aggregate happiness means that counteracting influences must have been present. One such factor is value orienta- tion. An increasing tendency for Norwegians to give priority to income and material possessions appears to have had an adverse effect on happiness towards the end of the last millennium.

Extreme nonresponse and response bias

Abstract: The article analyzes response bias in the Norwegian Monitor, a series of surveys carried out every second year since 1985, with a response rate of only 4 % in the last wave. One third of the respondents in a telephone interview completed the follow-up mail questionnaire. Their answers in the telephone interview are compared with those of the total telephone sample. Furthermore, results from the mail questionnaire are compared with population statistics and high-response surveys. Finally, the plausibility of nonresponse bias as an explanation regarding trends and correlations in the data is discussed. The conclusion is that even in this extreme case of nonresponse most results are not biased, suggesting that also survey data with very low response rates may have scientific value.

Class inequality and egalitarian reform

Abstract: Major studies of recruitment to higher education find the association with class to be stable over time, and on this basis conclude that egalitarian reforms have been ineffective. In contrast, measures of inequality for the same data show the distribution of attractive positions to have evened out considerably. The difference in results is explained by how the two sets of measures are affected by changes in the marginals of the class-education table, in particular the increased provision of higher education. It is argued that measures of inequality are more relevant for the question of the effectiveness of reform than measures of association, whether linear or loglinear.

Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites

Abstract: Black Americans are systematically undertreated for pain relative to white Americans. We examine whether this racial bias is related to false beliefs about biological differences between blacks and whites (e.g., “black people’s skin is thicker than white people’s skin”). Study 1 documented these beliefs among white laypersons and revealed that participants who more strongly endorsed false beliefs about biological differences reported lower pain ratings for a black (vs. white) target. Study 2 extended these findings to the medical context and found that half of a sample of white medical students and residents endorsed these beliefs. Moreover, participants who endorsed these beliefs rated the black (vs. white) patient’s pain as lower and made less accurate treatment recommendations. Participants who did not endorse these beliefs rated the black (vs. white) patient’s pain as higher, but showed no bias in treatment recommendations. These findings suggest that individuals with at least some medical training hold and may use false beliefs about biological differences between blacks and whites to inform medical judgments, which may contribute to racial disparities in pain assessment and treatment.

Faces of Inequality: Gender, Class, and Patterns of Inequalities in Different Types of Welfare States

Abstract: Research on welfare states and inequality has tended to be bifurcated, focusing either on class or on gender This paper combines gender and class in an analysis of patterns of inequalities in different types of welfare states in 18 countries Whereas a major dimension of class inequality can be described in terms of material standards of living, in the advanced Western countries it is fruitful to conceptualize gender inequality in terms of agency In analyses of gender as well as of class inequalities, welfare states have been seen as significant intervening variables However, major problems have emerged in attempts to devise typologies of welfare states that are of heuristic value in analyses of gender inequality as well as of class inequality This paper describes the development of gendered agency inequality during the period after the Second World War in 18 OECD countries in the arenas of democratic politics, tertiary education, and labor force participation Class inequality is measured in terms of disposable house income based on LIS data The paper develops a new typology of welfare states based on institutional structures of relevance for gender inequality as well as class inequality The combination of gender and class throws new light on the driving forces behind inequalities and on the role of welfare states in this context Gender inequality is conceptualized in terms of agency The paper presents a new typology of welfare states based on institutional structures of relevance for gender inequality as well as class inequality The combination of gender and class throws new light on the driving forces behind inequalities and on the role of welfare states in this context

Comparison of Hospital Mortality and Readmission Rates for Medicare Patients Treated by Male vs Female Physicians.

Abstract: Importance Studies have found differences in practice patterns between male and female physicians, with female physicians more likely to adhere to clinical guidelines and evidence-based practice. However, whether patient outcomes differ between male and female physicians is largely unknown. Objective To determine whether mortality and readmission rates differ between patients treated by male or female physicians. Design, Setting, and Participants We analyzed a 20% random sample of Medicare fee-for-service beneficiaries 65 years or older hospitalized with a medical condition and treated by general internists from January 1, 2011, to December 31, 2014. We examined the association between physician sex and 30-day mortality and readmission rates, adjusted for patient and physician characteristics and hospital fixed effects (effectively comparing female and male physicians within the same hospital). As a sensitivity analysis, we examined only physicians focusing on hospital care (hospitalists), among whom patients are plausibly quasi-randomized to physicians based on the physician’s specific work schedules. We also investigated whether differences in patient outcomes varied by specific condition or by underlying severity of illness. Main Outcomes and Measures Patients’ 30-day mortality and readmission rates. Results A total of 1 583 028 hospitalizations were used for analyses of 30-day mortality (mean [SD] patient age, 80.2 [8.5] years; 621 412 men and 961 616 women) and 1 540 797 were used for analyses of readmission (mean [SD] patient age, 80.1 [8.5] years; 602 115 men and 938 682 women). Patients treated by female physicians had lower 30-day mortality (adjusted mortality, 11.07% vs 11.49%; adjusted risk difference, –0.43%; 95% CI, –0.57% to –0.28%; P P Conclusions and Relevance Elderly hospitalized patients treated by female internists have lower mortality and readmissions compared with those cared for by male internists. These findings suggest that the differences in practice patterns between male and female physicians, as suggested in previous studies, may have important clinical implications for patient outcomes.

Linear versus logistic regression when the dependent variable is a dichotomy

Abstract: The article argues against the popular belief that linear regression should not be used when the dependent variable is a dichotomy. The relevance of the statistical arguments against linear analyses, that the tests of significance are inappropriate and that one risk getting meaningless results, are disputed. Violating the homoscedasticity assumption seems to be of little practical importance, as an empirical comparison of results shows nearly identical outcomes for the two kinds of significance tests. When linear analysis of dichotomous dependent variables is seen as acceptable, there in many situations exist compelling arguments of a substantive nature for preferring this approach to logistic regression. Of special importance is the intuitive meaningfulness of the linear measures as differences in probabilities, and their applicability in causal (path) analysis, in contrast to the logistic measures.