Multiple Treatment Groups Research Articles

Quantification of rat pre-pro-thyrotropin releasing hormone (TRH) mRNA by reverse transcription-polymerase chain reaction using external and internal standardisation

We have developed a quantitative reverse transcription polymerase chain reaction (RT-PCR) method, using both internal and external standardisation, to quantitate fg amounts of pre-pro-thyrotropin releasing hormone (pre-pro-TRH) mRNA in the paraventricular nucleus (PVN) of individual laboratory rats. A constant amount of internal standard is coamplified with both the cDNA of each unknown specimen and a dilution series of an identical RT-PCR generated external standard, allowing quantitation of the samples by interpolation from the external standard curve. Pre-pro-TRH mRNA levels in the PVN were reduced by thyroxine (T 4) treatment to 48% of those in control animals, and were increased by thyroidectomy to 155% of the control levels. By combining external and internal standardisation, our method allows multiple samples and treatment groups to be assayed concurrently, thereby eliminating inter-assay variability, whilst retaining the advantages of internal standardisation. It will facilitate further studies of the control of TRH gene expression in pathophysiological conditions.

Statistical Considerations for Multiplicity in Confirmatory Protocols

Statistical issues concerning multiple response criteria, multiple treatment groups, and multiple subgroups in clinical trials require careful attention in order to avoid an inappropriately high prevalence of chance findings, as well as to avoid unsatisfactorily low power to detect real treatment differences. An underlying goal is using a 0.050 significance level as often as possible for separate assessments while maintaining a 0.050 level for all assessments taken together, so statistical power is not compromised. For multiple response criteria, a useful assessment strategy is composite ranking as a single criterion first and then its individual components. Multiple treatment comparisons can often be effectively addressed with closed testing procedures with hierarchical evaluation. This hierarchy must be well specified since significance at its first stage is required before testing is allowed at the next stage. In most clinical trials, subgroups are of supportive interest after statistical significance for all patients is shown. A subgroup hierarchy, however, permits primary evaluation in conjunction with all patients through significance level spending function methods as in interim analyses, for example, the O’Brien-Fleming method. The rationale is the analogy between a subgroup hierarchy and the patient hierarchy at successive interim analyses. With this method, the significance level for all patients’ evaluation typically ranges between 0.040 and 0.045 and that for subgroups ranges from 0.005‐0.020. The methods outlined here for multiple response criteria, multiple treatment groups, and subgroups, or related counterparts, should be prespecified in the protocol for a clinical trial. If not in the protocol, they should be incorporated in the analysis plan prior to study unmasking.

Comparing Predictive Accuracy

Using research designs patterned after randomized experiments, many recent economic studies examine outcome measures for treatment groups and comparison groups that are not randomly assigned. By using variation in explanatory variables generated by changes in state laws, government draft mechanisms, or other means, these studies obtain variation that is readily examined and is plausibly exogenous. This paper describes the advantages of these studies and suggests how they can be improved. It also provides aids in judging the validity of inferences they draw. Design complications such as multiple treatment and comparison groups and multiple pre- or post-intervention observations are advocated.

Natural and Quasi-Experiments in Economics

Using research designs patterned after randomized experiments, many recent economic studies examine outcome measures for treatment groups and comparison groups that are not randomly assigned. By using variation in explanatory variables generated by changes in state laws, government draft mechanisms, or other means, these studies obtain variation that is readily examined and is plausibly exogenous. This paper describes the advantages of these studies and suggests how they can be improved. It also provides aids in judging the validity of inferences they draw. Design complications such as multiple treatment and comparison groups and multiple pre- or post-intervention observations are advocated.

The conduct and reporting of intervention studies

This commentary begins with a description of the various types of comparison or control groups that have been used in intervention studies and notes the need for researchers to meet and make recommendations about which types of comparison groups are most appropriate. I then discuss the importance of instruction and (a) present a list of instructional procedures that might be considered when evaluating or planning instruction during an intervention, (b) describe the need for researchers to provide implementation checklists for others to use, and (c) discuss the need for journals to provide fuller descriptions of the instruction in an intervention. There is also a discussion of two general problems that have emerged from reviewing this research: (a) the results obtained when standardized tests have been used in these studies are different from the results obtained when experimenter-developed comprehension tests have been used, and (b) there are no accepted procedures for deciding how many effect sizes to compute when conducting a meta-analysis when there are multiple treatment groups, multiple control groups, and multiple outcome measures.

Effects of management education: A quantitative synthesis

This meta-analysis synthesized the results of 22 studies of management education in institutional settings. The results indicate that the treatment's median effect size is .7—a fairly substantial effect. Several differential effects were noticed, including the experience level of the managers and the types of instrumentation and institutional setting. The general state of the evaluation literature shows the widespread lack of multiple treatment and control groups in measuring effects of management education programs.

Induction of ornithine decarboxylase in specific subpopulations of murine epidermal cells following multiple exposures to 12-O-tetradecanoylphorbol-13-acetate, mezerein and ethyl phenylpropriolate

Single applications of 12-O-tetradecanoylphorbol-13-acetate (TPA), mezerein or ethyl phenylpropriolate (EPP) to mouse skin at appropriate doses cause similar degrees of hyperplasia and comparable levels of induction of epidermal ornithine decarboxylase (ODC) activity. Multiple (n = 5) treatments with these agents, in contrast, resulted in large differences in induced ODC activity (TPA much greater than mezerein greater than EPP) with no differences in the degree of hyperplasia or [3H]thymidine pulse-labeling among the multiple treatment groups. To attempt to explain the cellular basis for the greater ODC-inducing ability of TPA relative to mezerein and EPP in chronic exposure protocols, immunocytochemical and flow cytometric analyses were performed. Immunocytochemistry using an ODC-specific polyclonal antibody revealed substantially different pattern of ODC-positive cells in chronically exposed epidermis than observed with single exposures. TPA treatment resulted in very pronounced immunostaining of the perifollicular cells, with little evidence of specific staining in the interfollicular epidermis mezerein treatment yielded staining in both interfollicular and some perifollicular areas, while EPP treatment produced the least amount of specifically stained cells, all of which were in the interfollicular epidermis. Flow cytometric analysis of keratinocytes isolated from chronically treated skin identified three distinct subpopulations that bound varying amounts of ODC antibody. Chronic treatment of CD-1 murine epidermis with TPA appeared to cause the expansion of an intermediate sized cell subpopulation that was not apparent with EPP or mezerein. Our results suggest that chronic treatment of murine epidermis with the potent complete tumor promoter TPA leads to the selective expansion of a keratinocyte subpopulation that is hyperinducible for ODC and may be identical to the cells in the perifollicular region previously identified. These observations also suggest that the weaker tumor promoters mezerein and EPP are less capable of causing expansion of this specific subpopulation, which may be an important target cell population for neoplastic transformation in mouse epidermis.

Incorporating historical controls in testing for a trend in multinomial proportions

Abstract For an experiment with multiple treatment groups and a historical control group, statistical tests for an increasing trend in proportion (across the treatment groups) are considered. There is a basic need for a meaningful interpretation of this ‘increasing trend’ in the multinomial case, and this is effectively done in terms of the underlying trait distributions for the different groups. In this context, for ‘trend alternatives’, asymptotically most powerful rank order tests for grouped data are considered, and these are then adapted by incorporation of historical controls with a Dirichlet distribution. The related asymptotic efficacy results are also presented in a unified manner.

Optimal design allocations for estimating area under curves for studies employing destructive sampling.

Optimal allocations of experimental resources for the estimation of integrals is considered for experiments that use destructive sampling. Given a set of sampling times, a minimum mean square error rule is given for the allotment of fixed experimental resources to the independent variable. The results are seen to be functionally dependent upon the pattern of underlying variability assumed in the model and upon the quadrature rule used to estimate the integral. Extensions to other optimality criteria, including a minimum mean absolute deviation criterion, and to cases involving multiple treatment groups, are also noted.