Letter to the Editor

Within the pharmaceutical industry it is common practice to transfer analytical methods from one laboratory to other laboratories. An experiment or interlaboratory study is performed to estimate the repeatability, the intermediate precision, and the reproducibility of the analytical method. These measures of precision are quantified by appropriate sums of variance components from an analysis of variance model describing the structure of the data. In the literature, several methods have been described for calculating approximate (closed-form) confidence intervals on sums of variance components, i.e., Welch, Satterthwaite, and modified large-sample (MLS). Comparisons between these methods have been performed for one-way and two-way classification analysis of variance models only. Interlaboratory studies though often need higher order classifications. Therefore, these methods for constructing confidence intervals are compared on the measures of precision from a specific three-way classification analysis of variance model that is frequently used for method transfer studies. Using a simulation study, the coverage probability for these methods is evaluated in situations where variance components may be estimated negatively with the standard moment estimates and where either the standard moment estimates are adjusted to zero or remain unadjusted. The MLS method is superior to the other two methods in case the standard moment estimates are used. If the adjusted moment estimates are used, then the method of Satterthwaite performs similar to the MLS method for many settings of the variance components and sample sizes but much better for some particular settings. The method of Satterthwaite performs better than the method of Welch for all the selected settings of variance components and sample sizes, irrespective of the standard or adjusted moment estimates.     

Letter to the Editor

Pharmaceutical Research -     

Letter to the Editor

Aims. To examine cannabis users’ patterns of use, their experiences of the positive and negative effects of use, their use of other substances and possible health risks, in the context of increased prevalence of use. Methods. A snowball sample of student cannabis users in the South East England (n?=?176) were interviewed with an extensive structured questionnaire that asked about frequency of use of cannabis, of other substances, of methods of use and of positive and negative effects of use. Findings. There were two common types of users; casual users who did not buy cannabis often and regular users who often bought cannabis and used it most days. Fewer users bought cannabis often and used it in a more controlled pattern. The effects of use were similar to those described by Tart [Tart, C. T. (). Marijuana Intoxication: Common Experiences. Nature, 226, 701–704], being predominantly positive and about relaxation and sensuality, although negative effects on mood and cognition were also experienced. Users tended to mix cannabis, tobacco and alcohol more than mixing with other drugs. The biggest health risk posed was tobacco use. Regular users showed more signs of dependence than casual or controlled users. Being in a road traffic accident whilst intoxicated was a strong predictor of other signs of dependence. Signs of dependence did not predict heavy use, which was instead most strongly predicted by seeing cannabis as one of life's main pleasures. Conclusions. Cannabis use has normalised, not all users use in problematic ways and use is moving away from other controlled drugs and towards alcohol and tobacco in a number of respects. There needs to be initiative to dissuade cannabis users from smoking tobacco. As with alcohol, those involved in accidents need to be questioned about their cannabis use and referred to drug services as required. Interventions for heavy cannabis use and dependence should be sensitive to the positive aspects of heavy use.