PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 4538910

A mathematical method for analysing questionnaires.

A Levine·P Roizen·P Rozé·H Christensen
View original source ↗Export metadata ↓

Abstract

Investigators using questionnaires are usually confronted with an enormous number of different responses whose significance with respect to a particular characteristic is not immediately clear. This paper presents a simple computational technique for determining the relative merits of each question and a score for each respondent. The rationalization for and the formalization of the method are discussed and some practical examples illustrate how it can be used. The strengths and weaknesses of the method are discussed in relation to those of other methods.

Explore related subjects

MathematicsMethodsSurveys and QuestionnairesJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

A Levine, P Roizen, P Rozé, H Christensen. 1972. A mathematical method for analysing questionnaires.. https://pubmed.ncbi.nlm.nih.gov/4538910/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed1992

Nonlinear response of biophoton emission to external perturbations.

By considering an exciplex system consisting of collective molecules in interaction with both the 'pumping' fields and the biophoton fields, the two-level exciplex model and the three-level exciplex model are presented. They are useful for the investigation of the quasi-stationary behaviour of biophoton emission, and biophoton emission as a dynamic process in the presence of external perturbations. Our theoretical results predict a series of nonlinear effects, such as chaos, fractal behaviour, and non-equilibrium phase transition. These effects characterize the coherence nature of living systems. In our approaches, there are two important quantities f and x, which can be used to mark the working points of the two-level and three-level exciplex systems. All the influences of external perturbations on the exciplex systems, e.g. change of temperature, the addition of agents, exposure to light, etc., can be interpreted as shifts of the working points of the systems, leading to a diversity of nonlinear response of biophoton emission. In addition, the agreements of the theoretical results and the corresponding experimental observations on biophoton emission from biological systems in the presence of external perturbations are demonstrated.

Mathematics↗
PubMed1992

Relationships between secondary structure fractions for globular proteins. Neural network analyses of crystallographic data sets.

The relationship between the fractions of protein secondary structural components as determined from X-ray crystallographic data by the procedures of Kabsch and Sander (KS) and of Levitt and Greer (LG) is analyzed by neural network analysis of these two tabulations of literature data. A linear relationship between the KS and LG reductions of X-ray data to secondary structure descriptors is demonstrated by a regression analysis of the relationships between these sets of structural parameters. Back-propagation neural network analysis was then used to derive equations for determination of the most probable fractions of beta-sheet, bend, turn, and "other" conformations given the fraction of alpha-helix in a globular protein. The deviation of the X-ray values for beta-sheet from that determined with these equations was shown to have a variance that exponentially decreased with increasing fraction of alpha-helix. A second neural network analysis showed that knowledge of both the alpha-helical and beta-sheet fractions in a protein significantly reduces the uncertainty in prediction of the other components of the secondary structure. These analyses provide insight into the nature of the data sets derived from crystal structures. Since these complications of crystal structure data are commonly used as reference information for quantitative evaluation of spectra (for example, FTIR, Raman, and electronic or vibrational circular dichroism) in terms of secondary structure, such internal correlations in the reference sets may have significant effects on the stability of spectroscopic analyses derived from them.

Mathematics↗
PubMed1992

Relation between the convergence temperatures Th* and Ts* in protein unfolding.

A challenge in understanding the thermodynamics of protein unfolding is to explain the 1979 puzzle posed by Privalov. Why do values of the specific enthalpy and specific entropy of unfolding both converge to common values at approximately the same temperature (Th* approximately equal to Ts*) when extrapolated linearly versus temperature? In 1986, a liquid hydrocarbon model gave an explanation for convergence of the specific entropies at Ts*: it happens because the contribution of the hydrophobic effect to the entropy of unfolding goes to zero at Ts*. The reason for convergence of the specific enthalpies at Th* and for the equality Th* approximately equal to Ts* has remained, however, a matter for speculation; recently, some explanations have been given that are based on models for polar interactions in protein folding. We show here that the relation Th* approximately equal to Ts* can be derived straightforwardly without making any assumptions either about polar interactions or about splitting the hydrophobic interaction into two terms--one for the "hydrophobic hydration" and the other for the residual effect, as suggested recently. Thus, the liquid hydrocarbon model explains both halves of Privalov's puzzle. A similar conclusion has been reached independently by A. Doig and D. H. Williams (personal communication). It has been proposed recently that a correction should be made for the relative sizes of a hydrocarbon solute and water when computing the thermodynamic properties of the hydrophobic interaction from a solvent transfer experiment. This correction affects the temperature at which the entropy of transfer equals zero, and it is important to evaluate its effect on the convergence temperature Ts*. We show that making the size correction does not change the conclusion, reached earlier, that the liquid hydrocarbon model explains the convergence of the specific entropies of protein unfolding.

Mathematics↗