DO JURORS HOLD AUDITORS TO A DIFFERENT NEGLIGENCE STANDARD UNDER U.S. GAAP AND IFRS?

In order to fulfill the requirements of East Carolina University’s Honors College, I created the research study described in this paper to examine the effects on auditor liability under United States Generally Accepted Accounting Principles compared to the International Financial Reporting Standards. The Financial Accounting Standards Board and the International Accounting Standards Board have been working towards convergence between U.S. GAAP, a rules-based system, and IFRS, a principles-based system. This research study examines whether potential jurors would hold auditors to a different negligence standard between rules-based and principles-based accounting. This study also explores how juror assessments of auditor responsibility differ when auditor liability is limited, as opposed to, unlimited. An experiment was conducted with students at a large state university representing jurors. I found evidence that auditor liability was held to a higher dollar value under unlimited liability and when relevant accounting standards were rules-based

Alcohol consumption and risk of uterine myoma: A systematic review and meta analysis

<div><p>Background</p><p>The published data about alcohol consumption and uterine myoma are scanty and controversial: some studies found positive association whereas other studies showed no association.</p><p>Objectives</p><p>To conduct a systematic review and meta-analysis to determine whether alcohol is a risk factor for myoma.</p><p>Search strategy</p><p>A MEDLINE/EMBASE search was carried out, supplemented by manual searches of bibliographies of the selected studies.</p><p>Selection criteria</p><p>Articles published as full-length papers in English. In the review we included all identified studies. Otherwise, the inclusion criteria for studies included in the meta-analysis were: a) case-control or cohort studies, reporting original data; b) studies reporting original data on the association between alcohol consumption and myoma; c) diagnosis of myoma was ultrasound or histological confirmed and/or clinically based.</p><p>Data collection and analysis</p><p>A total of 6 studies were identified for the review and 5 studies were included in the meta-analysis. The primary outcome was the incidence of uterine myoma in ever versus never alcohol drinkers and when data were available, we also analyzed categories of alcohol intake. We assessed the outcomes in the overall population and then we performed a subgroup analysis according to study design. Pooled estimates of the odds ratios (OR) with 95% confidence interval (CI) were calculated using random effects models.</p><p>Main results</p><p>The summary OR (95%CI) of myoma forever versus never alcohol intake was 1.12 (0.94–1.34) with significant heterogeneity. The summary OR for current versus never drinking was 1.33 (1.01–1.76) with no heterogeneity.</p><p>Conclusions</p><p>Ever alcohol consumption is not associated with myoma risk. Based on the data of two studies, current alcohol drinkers had a slightly borderline increased risk of diagnosis of myoma. In consideration of the very limited number of studies and the suggestion of a potential increased risk among current drinkers, further studies are required.</p></div

Study specific and summary odds ratio (OR) of uterine myoma for ever versus no alcohol intake.

<p>CI: confidence interval.</p

Flow chart of the selection of studies on alcohol intake and risk of uterine myoma included in the systematic review and meta-analysis.

<p>Flow chart of the selection of studies on alcohol intake and risk of uterine myoma included in the systematic review and meta-analysis.</p

Costs of treatments and adverse events in euro for each Health State.

<p>Costs of treatments and adverse events in euro for each Health State.</p

Structure of the microsimulation model at the individual level.

<p>Circle: event that does not determine a change of line of treatment. Rhombus: event that determine a change of line of treatment. HS: Health State. CHD: Coronary heart disease. CKD: Chronic kidney disease. OI: Opportunistic infection. VL: Viral load. § event that may lead to death. * Detectable viral load for two consecutive semesters. Patients enter the model being in first-line treatment (LPV/r or ATV+r). After each cycle, patients may change health state, die or experience events that may lead to a change in the line of treatment (patients in second-line had different treatment options that excluded those on first-line). Diarrhoea and hyperbilirubinemia may be experienced only by patients in first-line treatment, since these adverse events are associated with LPV/r and ATV+r therapies.</p

QALY variables related to HS, and events entered in the microsimulation model.

<p>HS: Health state; QALY: Quality-adjusted life years; CHD: Coronary heart disease; CKD: Chronic kidney disease; OI Opportunistic infection</p

Incremental cost effectiveness ratio plan, presenting the results of the probabilistic sensitivity analysis of LPV/r vs. ATV+r 1 regimens.

<p>Incremental cost effectiveness ratio plan, presenting the results of the probabilistic sensitivity analysis of LPV/r vs. ATV+r 1 regimens.</p

Incremental cost effectiveness ratio plan, presenting the results of the probabilistic sensitivity analysis of LPV/r vs. ATV+r 2 regimens.

<p>Incremental cost effectiveness ratio plan, presenting the results of the probabilistic sensitivity analysis of LPV/r vs. ATV+r 2 regimens.</p

Parameters used within the sensitivity analysis performed.

<p>CHD: Coronary heart disease; CKD: Chronic kidney disease; OI: Opportunistic infection; TC: Total cholesterol; HDL: High-density lipoprotein; HS: Health state; QALY: Quality-adjusted life years.</p>*<p>Ranges are: minimum and maximum or percentage variation of base-case values for uniform distributions; mean and standard deviation for normal distributions; alpha and beta are shape parameters for beta distributions.</p>‡<p>Risk values of diarrhoea, hyperbilirubinemia and opportunistic infections distributed according to a beta probability distribution.</p