Modelling Negative Binomial as a substitute model to Poisson for raters agreement on ordinal scales with sparse data

The Poisson distribution has been widely used for modelling rater agreement using loglinear models. Mostly in all life or social science researches, subjects are being classified into categories by rater, interviewers or observers and most of these tables indicate that the cell counts are mixtures of either too big values and two small values or zeroes which are sparse data. We refer to sparse as a situation when a large number of cell frequencies are very small. For these kinds of tables, there are tendencies for overdispersion in which the variance of the outcome or response exceeds the nominal variance, that is, when the response is greater than it should be under the given model or the true variance is bigger than the mean. In these types of situations assuming Poisson models means we are imposing the mean-variance equality restriction on the estimation. This implies that we will effectively be requiring the variance to be less than it really is, and also, as a result, we will underestimate the true variability in the data. Lastly, this will lead us to underestimating the standard errors, and so to overestimating the degree of precision in the coefficients. The Negative Binomial, which has a variance function, would be better for modelling rater agreement with sparse data in the table in order to allow the spread of the observations or counts. We observed that assuming Negative Binomial as the underline sampling plan is better for modelling rater agreement when there are sparse data in a limited number of example

A review of agreement measure as a subset of association measure between raters

Agreement can be regarded as a special case of association and not the other way round. Virtually in all life or social science researches, subjects are being classified into categories by raters, interviewers or observers and both association and agreement measures can be obtained from the results of this researchers. The distinction between association and agreement for a given data is that, for two responses to be perfectly associated we require that we can predict the category of one response from the category of the other response, while for two response to agree, they must fall into the identical category. Which hence mean, once there is agreement between the two responses, association has already exist, however, strong association may exist between the two responses without any strong agreement. Many approaches have been proposed by various authors for measuring each of these measures. In this work, we present some up till date development on these measures statistics

Conditional symmetry model as a better alternative to Symmetry Model for rater agreement measure

In almost all life or social science researches, subjects are classified into categories by raters, interviewers or observers. Many approaches have been proposed by various authors for analyzing the data or the results obtained from these raters. Symmetry and conditional symmetry models are models designed for square tables like the one arising from the raters results. Conditional symmetry model which possessed an extra parameter for the off-diagonal cells is a special case to symmetry. In this research work, we examined the effect of the extra parameter introduced by conditional symmetry model over that of symmetry on structure of agreement as well as their fittings. Generalized linear model (GLM) approach was used to model the loglinear model forms of these models with empirical examples. We observed that conditional symmetry based on it extra parameter gave a tremendous improvement to the significant level of the test statistics over that of its symmetry model counterpart, hence conditional symmetry model is better for raters agreement modelling which require symmetric table

Post-harvest technology change in cassava processing: a choice paradigm

Open Access Article; Available online: 27 Jan 2020This study employed a choice model to examine the factors influencing the choice of post-harvest technologies in cassava starch processing, using a sample of five hundred and seventy (570) processors in the forest and guinea savanna zones of Nigeria. In addition, the profitability of various post-harvest technologies in the study area was assessed using the budgetary technique while the impact of improved post-harvest technology on processors’ revenue and output was analysed using the average treatment effect model. Sex of the processor, processing experience, income, and cost of post-harvest technology, the capacity of post-harvest technology and access to credit amongst others significantly influence the choice of post-harvest technologies. Although the use of improved post-harvest technology comes with a high cost, the net income from its use was higher than the other types of post-harvest technologies, suggesting that the use of improved techniques was more beneficial and profitable. In addition, using improved post-harvest technology had a positive and significant effect on output and income. These findings shows that investment in improved post-harvest technologies by cassava starch processors and other stakeholders would increase income, thus, improving welfare

Data analysis on physical and mechanical properties of cassava pellets

In this data article, laboratory experimental investigation results carried out at National Centre for Agricultural Mechanization(NCAM) on moisture content,machine speed,die diameter of the rig, and the outputs (hardness,durability,bulk density,and unit density of the pellets) at different levels of cassava pellets were observed. Analysis of variance using randomized complete block design with factorial was used to perform analysis for each of the outputs: hardness,durability,bulk density,and unit density of the pellets. A clear description one ach of these outputs was considered separately using tables and figures. It was observed that for all the output with the exception of unit density,their main factor effects as well as two and three ways interactions is significant at 5% level.This means that the hardness,bulk density and durability of cassava pellets respectively depend on the moisture content of the cassava dough,the machine speed,the die diameter of the extrusion rig and the combinations of these factors in pairs as well as the three altogether .Higher machine speeds produced more quality pellets at lower die diameters while lower machine speed is recommended for higher die diameter.Also the unit density depends on die diameter and the three-way interactiononly.Unit density of cassava pellets is neither affected by machine para- meters nor moisture content of the cassava dough.Moisture content of cassava dough,speed of the machine and die diameter of the extrusion rigare significant factors to be considered in pelletizing cassava to produce pellets.Increase in moisture content of cassava dough increase the quality of cassava pellets

A Note on the Minimax Distribution

We introduce a one parameter probability model bounded on (0, 1) support called One Parameter Minimax distribution which is a special case of both the Kumaraswamy distribution and Beta distribution. Its statistical properties are systematically explored; we provide explicit expressions for its moments, quantile function, reliability function and failure rate. The method of maximum likelihood estimation was used in estimating its parameter. The proposed model can be used to model data sets with increasing failure rate

Cochran–Mantel–Haenszel Test for Repeated Tests of Independence: An Application in Examining Students’ Performance

From the result of graduate of ten departments in Faculty of Science, University of Ilorin for 2011/2012 academic session, data on final cumulative grade point average (Final Grade); department (ten departments of the faculty); age at entry (below or 20 years and above 20 years) and sex (male and female) are analyzed using Cochran-Mantel-Haenszel statistics. Odds of a student graduating with Second Class Upper and above (0.5270) is about half of graduating with Second Class Lower and below. This implies that the final grade is approximately symmetrical about two groups. The first group are those with Second Class Lower and below (Low Grade) while the other is for those with Second Class Upper and above (High Grade). Breslow-Day and Tarone’s statistics show that the null hypothesis of homogeneity of odds ratio across the departments is not rejected for both age at entry and sex. This implies that the odds ratio across the ten departments (relating to age at entry & final grade and sex & final grade) are all equal. Cochran’s and Mantel-Haenszel statistics reveals the final grade of students (Low Grade or High Grade) is not associated with both sex and age students at entry. The odds in favour of a student whose age is less than 20 years graduating with Low Grade (Pass, Third Class, and Second Class Lower) is 0.865 while it is 0.670 for male students graduating with lower grade. Keywords: Test of Independence, Students’ Performance, Cochran-Mantel-Haensze

Drying kinetic of industrial cassava flour: Experimental data in view

In this data article,laboratory experimental investigation results on drying kinetic properties:the drying temperature(T), drying air velocity (V) and de watering time(Te),each of the factors has five levels, and the experiment was replicated three times and the output: drying rate and drying time obtained,were observed.The experiment was conducted at National Centre for Agricultural Mechanization (NCAM)for a period of eight months,in 2014. Analysis of variance was carried out using randomized complete block design with factorial experiment on each of the outputs:drying rate and drying times of the industrial cassava flour.A clear picture one ach of these out puts was provide deseparately using tables and figures. It was observed that all the main factors as well as two and three ways interactions are significant at5%level for both drying time and rate. This also implies that the rate of drying grated unfermented cassava mash, to produce industrial cassava flour,depend on the de watering time (the initial moisture content),temperature of drying,velocity of drying air as well as the combinations of these factorsal together.It was also discovered that all the levels of each of these factors are significantly difference from one another.In summary,the b time of drying is a function of the de watering time which was responsible for the initial moisture content. The higher the initial moisture content the longer the time of drying, and the lower the initial moisture content, the lower the time of drying.Also,the higher the temperature of drying the shorter the time of drying and vice versa.Also,the air velocity effect on the drying process was significant. As velocity increases, rate of drying also increases and vice versa.Finally,it can be deducedthatthedryingkineticsareinfluenced bythesepro- cessing factors

Some Basic Statistical Properties of the Transmuted Burr X Distribution

In this article, the Burr X distribution was extended using the transmuted family of distributions. Some basic statistical properties of the resulting Transmuted Burr X distribution were established while the method of maximum likelihood was proposed for parameter estimatio

The Transmuted Inverse Exponential Distribution

This article introduces a two-parameter probability model which represents another generalization of the Inverse Exponential distribution by using the quadratic rank transmuted map. The proposed model is named Transmuted Inverse Exponential (TIE) distribution and its statistical properties are systematically studied. We provide explicit expressions for its moments, moment generating function, quantile function, reliability function and hazard function. We estimate the parameters of the TIE distribution using the method of maximum likelihood estimation (MLE). The hazard function of the model has an inverted bathtub shape and we propose the usefulness of the TIE distribution in modeling breast cancer and bladder cancer data sets