Monte Carlo theoretical trials of methods for assessing statistical significance for differences between adjusted odds ratios

Odds are generally defined as the number of successes divided by the number of failures in a given number of trials. An odds ratio is the ratio of one odds divided by another. Odds ratios can be adjusted to reflect associations with the outcome independently of the influence of associations with other variables. These are adjusted odds ratios. There are several well known methods for comparing odds ratios and testing for statistically significant differences between them. Analogous methods for adjusted odds ratios are not well known or well documented. One method for comparing adjusted odds ratios is explained by Hosmer and Lemeshow (Applied logistic regression, 2000). This method is used for the odds ratios for two variables from the same data set. The purpose of this analysis was to apply this method to a different situation: comparing odds ratios for the same variable from two different data sets. Monte Carlo trials were used to assess the performance of the method and these indicated the method performed well.     

Managers’ psychological diversity climate and fairness: The utility and importance of diversity management in the hospitality industry

ABSTRACT

Despite corporate investments in diversity management programs, there is a dearth in the literature that examines managers' attitudes toward diversity management practices. This is a glaring gap in the literature because the success of diversity management programs is highly depend on managers. A survey was distributed to hotel managers from properties in the southern United States. The results showed that psychological diversity climate predicted the perceived utility and importance of diversity management, and these relationships were mediated by the fairness of diversity management. These results suggest that psychological diversity climate has an impact on attitudes toward diversity management practices.     

When does economic model type become a decisive factor in health technology appraisals? Learning from the expanding treatment options for relapsing–remitting multiple sclerosis

Objectives: Specific economic model types often become de facto standard for health technology appraisal over time. Markov and discrete event simulation (DES) models were compared to investigate the impact of innovative modeling on the cost-effectiveness of disease-modifying therapies (DMTs) in relapsing–remitting multiple sclerosis (RRMS). Fingolimod was compared to dimethyl fumarate (DMF; in highly active [HA] RRMS), alemtuzumab (in HA RRMS) and natalizumab (in rapidly evolving severe RRMS). Comparator DMTs were chosen to reflect different dosing regimens.

Materials and methods: Markov and DES models used have been published previously. Inputs were aligned in all relevant respects, with differences in the modeling of event-triggered attributes, such as relapse-related retreatment, which is inherently difficult with a memoryless Markov approach. Outcomes were compared, with and without different attributes.

Results: All results used list prices. For fingolimod and DMF, incremental cost-effectiveness ratios (ICERs) were comparable (Markov: £4206/quality-adjusted life year [QALY] gained versus DES: £3910/QALY gained). Deviations were observed when long-term adverse events (AEs) were incorporated in the DES (Markov: £25,412 saved/QALY lost, versus DES: £34,209 saved/QALY lost, fingolimod versus natalizumab; higher ICERs indicate greater cost-effectiveness). For fingolimod versus alemtuzumab, when relapse-triggered retreatment was included in the DES, large cost differences were observed (difference between incremental cost is £35,410 and QALY is 0.10).

Limitations: UK payer perspective, therefore societal approach was not considered. Resource utilization and utilities for both models were not derived from the subpopulations; as the focus is on model type, input limitations that apply to both models are less relevant.

Conclusions: Whilst no model can fully represent a disease, a DES allows an opportunity to include features excluded in a Markov structure. A DES may be more suitable for modeling in RRMS for health technology assessment purposes given the complexity of some DMTs. This analysis highlights the capabilities of different model structures to model event-triggered attributes.     

Overlooked encounters: young tourists' experiences at dark sites

This research note reviews the existing literature comprised of dark tourism articles and chapters mentioning children. Publications meeting the search criteria were few. Accordingly, we offer possible reasons for the scarcity of research on children in dark tourism, including the legal constraints when researching with minors, the academic risk in undertaking a new field of research, and the substantial expertise needed to engage children in studies. We conclude with the compelling reasons to undertake such research: to inform interpretation of emotionally provocative sites for children, to understand and mitigate children's psychological distress at dark sites, and to advance theoretical work on children as tourists.     

Are services advertised differently? An analysis of the relationship between product and service types and the informational content of their advertisements

This study examines the informational content of service and product advertisements and analyses the relationship between the amount and type of information in an advertisement and the type of product or service being advertised. The influence that service characteristics have on advertising strategy is still not well understood. One theory is that services need to be more tangible in order to assist in the consumer decision-making process and advertising can assist with this by providing factual information. The purpose of this paper is to establish whether this theory is recognized and adopted in advertising practice. This is achieved by performing a content analysis. The results indicate that product advertisements contain more information than services, which indicates a discrepancy between advertising theory and practice. The results also prove that there are variances in the amount and type of information included in product and service advertisements. The paper examines these variances and applies existing classification frameworks to explain them. Areas for further research are also identified.     

Do boards know when they hire a CEO that is a good match? Evidence from initial compensation

Are CEO initial compensation packages based on variations in the expected match quality of the hiring firms? Using CEO tenure as a proxy for expected match quality, and a sample of CEO turnovers between 1992 and 2006, we find that CEOs that experience good matches, defined as tenures exceeding four years, have higher initial compensation packages. We also find evidence from exogenous switching regression models that inside CEOs receive a higher good match premium than outside CEOs. To account for economic and regulatory changes across our sample period, we divide our sample into three subsamples: 1992–1997, 1998–2002, and 2003–2006, and repeat our analyses. Even though the positive relation between expected match quality and initial compensation persists across all periods, we find that the good match premium for inside and outside CEOs does not differ in the post-2002 period. We attribute this result to increased board independence and changes in regulation (Sarbanes–Oxley) in the post-2002 sample period.