Evaluating Orthodontic Awareness Study
Added on 2020-05-08
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THE SCIENTIFIC METHODIn this article we critique a journal article related to application of statistical tests, typically t-test, analysis of variance(ANOVA) and regression analysis. The critique is performed with respect to the strengths and weaknesses of the scientific research and whether the conduct and findings of the research have been communicated effectively using the scientic jargon.Keywords:t-test, regression, anova, statisticsINTRODUCTIONThe scientific method is the name given to a series of procedures for obtaining new knowledge or updating existing knowledge about the varied phenomena which typically involves empirical and measurable or verifiable source of observation. The father of scientific methodology is said by someto be the Arab polymath Ibn al-Haytham who first argued the importance of questioning phenomenaand validating them through formally testing them. The principal steps involved in the scientific method are:(i)detailed observation of events or phenomena, (ii) asking relevant questions about the cause and/or effect of the phenomena, (iii) formulating testable hypotheses based on the observations (iv) develop testable predictions based on the hypotheses framed (v) testing the validity of the predictions using empirical and falsifiable testing procedures (vi) formulating effective theories, if the tests in the previous step are positive/ reformulate hypiotheses and predictions and retest those. Thus, we see that scientific method is more of a cyclic and continuous process over time.(Science Made Simple. 2016). The scientific method, at least since the time of Galileo, has produced innumerable advancements in human knowledge and thinking, the fruits of which we are enjoying at the present moment. In this project, though, we look and critique at the scientific method with reference to the statistical perspective in a typical experimental setup, takinga published journal article for our reference.t-TEST, ANOVA AND REGRESSION ANALYSIS The three most prominent statistical terms that are being used in practice in statistical analyses, and are being critically examined with respect to their application in this report are: the t-test, analysis of variance(ANOVA) and regression analysis. It is important to know the details of these three terms before we try to critique the journal article. In a sense, all the three terms can be included under the broad category of regression analysis, which is used to compare the statistical difference between two or more different samples or variables.(Paret, M., 2016), (Lomax, R. G. 2007)Typically, the analysis is used to find out the relationship(s) between one dependent and one or more independent variables in a population. In regression analysis, the dependent variable is assumed to be a function of the independent variables with respect to certain parameters, the number of which depends of the type of regression we use, like linear or non-linear or multilinear. In mathematical terminology, we can say that regression analysis hinges on two things: (i)Correlation, or the problem of finding the form of the function fwhere Y=f(Xi,βi)(1) where Yis the dependent variable and Xiare dependent variables, βibeing the parameters which is usually determined in linear and general linear cases by a factor known as correlation coefficent
which is a ratio of product of covariances(deviation from means) to the product of standard deviations In this step, an additional terminology used is the error in prediction, denoted by εiwhichis minimized by a method commonly known as method of least squares.(ii) The testing of statistical significance of the above estimated function by calculating the conditional probability of the model being false and comparing the obtained value with that of a known standard probability distribution. Two additional terminologies used in this step are the null and alternative hypothesis. The null hypothesis is the assumption that the dependency of the dependent variable on the independent variable is not real but accidental and the alternative hypothesis is that the dependency is actual. In this context, the two most widely used probability distributions are the t-distribution and F-distribution. When the t-distribution is used, the statistical test is said to be a t-test, and when the F-distribution is used, the test is said to be an F-test.The analysis of variance(ANOVA) is determining the interdependence and statistical difference between a set of more than two variables using an F-test applied to the ratio of variance between thegroup of interdependent variables and variance within of group of variables. Note that the statisticaltests like t-test and F-test are not limited only to regression analysis, rather can also be performed onsample statistics which are assumed to follow the Student’s-t or Snedecor-F distribution.(NLREG., 2017), (Montgomery, D. C. 2012)In addition, for the analysis that we will use in this article, we also need some terminology from the sampling theory. The most common sampling methods used in experiments are: simple random sampling, stratified random sampling and multistage random sampling. In simple random sampling,each and every unit in the population is equally likely to be a part of the sample chosen. In stratifiedrandom sampling, the population is stratified, or classified beforehand into strata or classes based oncertain parameters and then, the sample is constructed by simple random sampling from amongst the strata. In multistage random sampling, the sample is chosen in multiple steps. This type of sampling is quite useful in cases where location based sampling is essential. In this type of samplingthe population is first divided into regions from which the first simple random sampling is done. The second stage consists of simple random sampling from dividing the hitherto divided regions into further smaller regions, and so on. Thus, in this type of sampling, we are more localising the population to be sampled.(Yale University ., 2017)THE ARTICLE CHOSEN FOR CRITICAL ANALYSISThe article that is chosen for this critical report is Pandey, M., Singh, J., Mangal, G., Yadav, P.,(2014),Evaluation of awareness regarding orthodontic procedures among a group of preadolescents in a cross-sectional study, Journal of International Society of Preventive and Community Dentistry,4(1),44-47. The article is an open access article, available on PubMed Centralwith PMCID:PMC4015160. In the article, statistical analysis is done regarding the awareness and know-how of orthodontic and other dental procedures among a group of preadolescents from rural and urban areas in Bilaspur district, Chattisgarh State, India. The objective of the paper says that thestudy was conducted as there was a high prevalence of malocclusion, which is a dental anomaly characterized by large abnormalities in the tooth position. The method employed by the authors of the paper was a cross-sectional study of about 1010 subjects(students) with average age somewhere around 13.02 years with standard deviation of 2.1 years using a questionnaire consisting of
questions pertaining know how of orthodontical procedures. The questionnaire was validated by using a pilot study consisting of nine items. Finally, to test the statistical significance, t-test and ANAOVA were conducteed at a significance level of 0.05. The broad results of the study were that students aged 14 years were more aware than other students, that girl students were significantly more aware of the orthodontic procedures and that students from urban background were similarly more aware than their rural counterparts.THE EXPERIMENTAL DESIGN USED IN THE ARTICLEThe method of design of the study used by the authors requires some mention. The Methods sectionof the article says that first, an epidemological survey was taken in the Bilaspur district during the period between September and December, 2013; and then later a multistage random sampling was done to select six schools consisting of three in urban and three in rural areas in the same district. We see that preliminary epidemological survey, done in this case is quite important, as it helps to determine the local variations amongst the population effectively. Sampling before assessing the local properties of the population may lead to enormous difficulties in proper data sampling and may even lead to biased sample. The next thing we note is the use of multistage random sampling toselect the six schools. Note that this is a very crucial part of the reseearch. If simple random sampling or, stratified random sampling would have been made, there could have been drastic changes in the result. We note that the method adopted by the authors is well suited to the purpose, as the population that is used to study is a very large one, and simple random sampling could be representative of a very small part of population. Stratified sampling, though better than simple random sampling in this case, gives the problem of stratification of the population, which is another complex issue having various parameters. Thus, the via media solution is to employ multistage random sampling that effectively tries to capture the population of Bilaspur district. We also note that a dual stratification has also been done by the authors by including equal samples from urban and rural areas. This is because, the urban students, having good access to modern information, maybe well equipped with orthodontic procedures, whereas, those with a rural background may not be as aware as their urban counterparts. Thus, to ensure evenness, equal samples were selected from both the urban and rural areas. We also note that pilot study was conducted to validate the questionnaire beforehand. Pilot study is a small scale reliability test of the sample to evaluate the feasibility, time, cost, adverse events, and statistical variability of the sample. This is quite essential,because, in spite of the precautions taken while choosing the sample, like multistage sampling and stratification into urban and rural parts, it may so happen that the sample is thoroughly biased, for example, it may so happen that a particular school chosen may be the only one where the students are exceptionally educated as regards dental procedures due to the fact of there being a qualified dentist and better infrastructural facility in the school and hence report to the questionnaire more faithfully and correctly in comparison with other schools, where the students may just randomly guess the answer to questionnaires based on their whims and fancies. To ensure fairness, a pilot study is essential before embarking to the full detailed questionnaire. The article states that the intra-examiner reliability factor, κ =0.87. We note that there is a good intra-examiner reliability, as the cohen’s kappa is close to 1.(Sapiens 2010).Now, the authors state that after the pilot study was performed amongst the chosen samples, the main sample was chosen excluding those undergoing orthodontic treatments. This latter step is added to ensure unbiasedness, as those students would be naturally more aware of orthodontic procedures.
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