Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

THE IMPLICATIONS OF CHOOSING "NO RACE" ON THE SALIENCE OF HISPANIC IDENTITY: How Racial and Ethnic Backgrounds Intersect among Hispanic Adolescents

Using data from the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative sample of youth from 7th to 12th grades, we examined how racial and ethnic identification overlap among Hispanic adolescents. We evaluated the relative proximity between race and ethnic identifiers among Hispanics. Empirical analyses suggest that the racial identification of other students at school has a significant impact on the odds of choosing particular racial identifiers. Both Hispanic and non-Hispanic schoolmates' racial identification is related to the racial identification of Hispanic adolescents. We also find evidence that both ethnicity and race are distinct stratifiers among Hispanics. Overall, our findings support the notion that Hispanic may be a more meaningful "racial" identity than black, white, or other, but we also find that racial identification and ethnic background are still important and meaningful dividers among Hispanic youth.     

Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

What Do Grandmothers Think about Self‐esteem? American and Taiwanese Folk Theories Revisited

The study investigates European American and Taiwanese grandmothers’ folk theories of childrearing and self‐esteem, building on an earlier comparison of mothers from the same families. Adopting methods that privilege local meanings, we bring grandmothers’ voices into the conversation about childrearing, thereby contributing to a deeper understanding of intergenerational nuances in folk theories. In each cultural case, 16 grandmothers of 3‐year‐olds participated in in‐depth interviews that were customized according to local communicative norms. Although self‐esteem emerged as a central organizing concept in the folk theories of European American mothers, grandmothers spoke in two voices, either echoing their daughters or invoking a counter‐discourse of wariness towards self‐esteem. By contrast, Taiwanese mothers and grandmothers resembled one another—but differed from their American counterparts—in treating self‐esteem as peripheral in childrearing. Results contribute to the growing consensus that self‐esteem is a culture‐specific childrearing goal and suggest that the European American tendency to valorize self‐esteem varies by generation.     

Risk,trust and knowledge networks in farmers’ learning

This study reports on New Zealand dairy farmers’ access to and use of information as mediated through conditions of risk and trust within the context of their interpersonal social networks. We located participants’ reports of their information use within their perceived environments of trust and risk, following Giddens's [1990. The consequences of modernity. Polity Press, Stanford, CA] typology of trust and risk in pre-modernity and modernity. The research participants were constant users of interpersonal and print information from numerous sources, and monitored their incoming data in the light of strategic needs, reflecting their roles as both farming practitioners and business owners. Socio-spatial knowledge networks (SSKNs) combine individuals’ explanatory cognitive models of information acquisition and use with a micro-geographical analysis of their interpersonal networks. The participants showed characteristics of pre-modern, modern and even post-modern society in respect of their use of complex interactional forms, as well as a blending of individualistic and communitarian practices and concerns in their professional and personal lives.     

Ninth-Grade Students' Attitudes Toward Nontraditional Occupations

This study explored how students choose careers, their attitudes toward vocational education, and whether or not they would consider enrolling in a nontraditional vocational education program.     

Setting operational goals for corporate social responsibility

In this article the author argues that more formality in social responsibility planning efforts is a concept which is extremely pertinent in today's conditions. Rewards will accrue to the organization that can move beyond aesthetic objectives and achieve operationality in social responsibility goal setting. This requires, basically, the application of techniques that have proved to be successful in MBO programs. By translating broadly stated social objectives into goals that are clear, concise, time related and cost related, management will inject an increased measure of integrity into its planning process, improve social responsibility programs, assure future successes in the social performance arena, facilitate the appraisal of management personnel, and enhance the organization's credibility with its multiple publics. Positive benefits will flow to the organization, its immediate publics, and to the society at large as a consequence of operational planning methods as described herein.     

Recent trends in Hispanic immigration to the United States

Recent patterns of Hispanic immigration to the United States are examined using data from the U.S. Immigration and Naturalization Service. "From 1960 to 1978 Hispanic immigration increased significantly, reflecting the general acceleration in total immigration to the United States. Demographic trends reveal that Hispanic immigrants are increasingly working-age women. Their occupation composition is primarily blue collar, with operatives emerging as the predominant job category during the 1970s." The authors note that these immigrants settle primarily in a small number of urban centers of Hispanic population and culture in the United States, and thus the effects of immigration will be concentrated on the low-skill segment of particular urban labor markets that already contain large numbers of Hispanic workers.