scholarly journals Sample size for the estimation of Pearson’s linear correlation in crotalaria species

2019 ◽  
Vol 54 ◽  
Author(s):  
Marcos Toebe ◽  
Letícia Nunes Machado ◽  
Francieli de Lima Tartaglia ◽  
Juliana Oliveira de Carvalho ◽  
Cirineu Tolfo Bandeira ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Sample Size ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Correlation Coefficients ◽  
Crotalaria Juncea ◽  
Species Pairs ◽  
Precision Level ◽  
Highly Correlated ◽  
Crotalaria Spectabilis

Abstract: The objective of this work was to determine the necessary sample size to estimate Pearson’s linear correlation coefficients of four species of crotalaria at precision levels. The experiment was carried out with Crotalaria juncea, Crotalaria spectabilis, Crotalaria breviflora, and Crotalaria ochroleuca, during the 2014/2015 crop year. Eight crotalaria traits were evaluated in 1,000 randomly collected pods per species. For each species, the correlation coefficients were estimated for the 28 pairs of traits, and the sample size necessary to estimate the correlation coefficients was determined at four precision levels [0.10, 0.20, 0.30, and 0.40 amplitudes of the 95% (CI95%) confidence interval] by resampling with replacement. The sample size varies between crotalaria species and, especially, between pairs of traits, as a function of the magnitude of the correlation coefficient. At a certain precision level, the smallest sample size is required to estimate the correlation coefficients between highly correlated traits and vice-versa. To estimate the correlation coefficients with CI95% of 0.20, 10 to 440 pods are required, depending on the species, pairs of traits, and magnitude of the correlation coefficient.

A selection of remarks on the measurement of correlations between variables of a panel data structure

2021 ◽  
Vol 66 (5) ◽  
pp. 7-25
Author(s):  
Mieczysław Kowerski ◽  
Jarosław Bielak
Keyword(s):  
Panel Data ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Correlation Coefficients ◽  
Data Dependencies ◽  
Construction Companies ◽  
Advantages And Disadvantages ◽  
Warsaw Stock Exchange

Many articles featuring panel data modelling tend to begin their considerations with an introduction of the Pearson linear correlation coefficients matrix between the analysed variables. The aim of the article is to prove such an approach unsuitable in the analysis of panel data dependencies. Instead, an attempt has been made to propose a more appropriate measure – a correlation coefficient between the empirical and fitted values of the dependent variable of the estimated panel model (with fixed or random effects) in relation to the variable whose dependency towards the dependent variable is being studied. Pearson’s linear correlation coefficient does not reflect the basic advantage of panel data, which is the ability to provide information about the dependencies of the studied phenomena simultaneously in time and space. The fact that one observation relates to object i during period t and another to object j during period t + 1 is irrelevant for the calculation of the coefficient. Pearson’s coefficient, however, can be used when conducting sub-calculations in panel data analysis. The presented considerations have been illustrated by the calculations of the relationships between the structure of capital and the profitability and size of 17 construction companies listed on the Warsaw Stock Exchange in the years 2009–2018 (170 observations) which created a balanced panel. A specification of the advantages and disadvantages of the proposed solution was formulated on the basis of the calculations.

Breed and environmental effects on lamb production in Nigeria

1981 ◽  
Vol 96 (1) ◽  
pp. 9-15 ◽  
Author(s):  
V. Buvanendran ◽  
I. F. Adu ◽  
B. A. Oyejola
Keyword(s):  
Body Weight ◽  
Environmental Factors ◽  
Least Squares ◽  
Correlation Coefficient ◽  
Environmental Effects ◽  
Correlation Coefficients ◽  
Correction Factors ◽  
The Cross ◽  
Highly Correlated ◽  
Least Squares Estimates

SUMMARYTwo indigenous breeds of sheep in Nigeria, the Yankasa and Uda and crosses of these with exotic breeds, were evaluated for lamb weights at birth, 3 months and 6 months of age and for adult ewe weight. The cross-bred lambs were significantly (P < 0·05) heavier than the indigenous breeds at all ages. Differences among the indigenous breeds were not significant. Mature ewe weight was 40·8 kg in the cross-bred and 36·0 and 31·1 kg in the Uda and Yankasa respectively, differences between all breeds being significant (P <0·05). Lamb productivity (lamb weight per kg of ewe metabolic body weight) estimates demonstrated that the differences between breeds were small.Least-squares estimates of effects of environmental factors on lamb performance showed that type of birth and age of dam were important for lamb weights at the three ages. Season and sex also had significant effects on birth and 6-month weights respectively. Correction factors for lamb weights were derived from least-squares estimates.The correlation coefficient between birth and 3-month weight was significant in all breeds and ranged from 0·39 to 0·55. Three-month and 6-month weights were highly correlated with estimates of correlation coefficients ranging from 0·71 to 0·74. Repeatability estimates of birth, 3·month, 6·month and ewe weights, all as traits of the ewe in the Yankasa, were 0·25, 0·21, 0·09 and 0·48, respectively.

scholarly journals Weighted Maximum Likelihood Correlation Coefficient to Handle Missing Values and Outliers in Data Set

2021 ◽  
Vol 20 ◽  
pp. 415-430
Author(s):  
Juthaphorn Sinsomboonthong ◽  
Saichon Sinsomboonthong
Keyword(s):  
Missing Data ◽  
Maximum Likelihood ◽  
Sample Size ◽  
Correlation Coefficient ◽  
Missing Values ◽  
Mean Squared Error ◽  
Correlation Coefficients ◽  
Median Percentage ◽  
Data Set ◽  
Median Correlation

The proposed estimator, namely weighted maximum likelihood (WML) correlation coefficient, for measuring the relationship between two variables to concern about missing values and outliers in the dataset is presented. This estimator is proven by applying the conditional probability function to take care of some missing values and pay more attention to values near the center. However, outliers in the dataset are assigned a slight weight. These using techniques will give the robust proposed method when the preliminary assumptions are not met data analysis. To inspect about the quality of the proposed estimator, the six methods—WML, Pearson, median, percentage bend, biweight mid, and composite correlation coefficients—are compared the properties in two criteria, i.e. the bias and mean squared error, via the simulation study. The results of generated data are illustrated that the WML estimator seems to have the best performance to withstand the missing values and outliers in dataset, especially for the tiny sample size and large percentage of outliers regardless of missing data levels. However, for the massive sample size, the median correlation coefficient seems to have the good estimator when linear relationship levels between two variables are approximately over 0.4 irrespective of outliers and missing data levels

scholarly journals The statistical studies of the inner boundary of plasma sheet

2011 ◽  
Vol 29 (2) ◽  
pp. 289-298 ◽  
Author(s):  
J. B. Cao ◽  
W. Z. Ding ◽  
H. Reme ◽  
I. Dandouras ◽  
M. Dunlop ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Plasma Sheet ◽  
Radial Distance ◽  
Correlation Coefficients ◽  
Geosynchronous Orbit ◽  
Direct Observations ◽  
The Earth ◽  
Night Side ◽  
Statistical Studies ◽  
Highly Correlated

Abstract. The penetration of plasma sheet ions into the inner magnetosphere is very important to the inner magnetospheric dynamics since plasma sheet ions are one of the major particle sources of ring current during storm times. However, the direct observations of the inner boundary of the plasma sheet are fairly rare due to the limited number of satellites in near equatorial orbits outside 6.6 RE. In this paper, we used the ion data recorded by TC-1 from 2004 to 2006 to study the distribution of inner boundary of ion plasma sheet (IBIPS) and for the first time show the observational distribution of IBIPS in the equatorial plane. The IBIPS has a dawn-dusk asymmetry, being farthest to the Earth in the 06:00 08:00 LT bin and closest to the Earth in the 18:00–20:00 LT bin. Besides, the IBIPS has also a day-night asymmetry, which may be due to the fact that the ions on the dayside are exposed more time to loss mechanisms on their drift paths. The radial distance of IBIPS decrease generally with the increase of Kp index. The mean radial distance of IBIPS is basically larger than 6.6 RE during quiet times and smaller than 6.6 RE during active times. When the strength of convection electric field increases, the inward shift of IBIPS is most significant on the night side (22:00–02:00 LT). For Kp ≤ 0+, only 16% of IBIPSs penetrate inside the geosynchronous orbit. For 2 ≤ Kp < 3+, however, 70% of IBIPSs penetrate inside the geosynchronous orbit. The IBIPS has weak correlations with the AE and Dst indexes. The average correlation coefficient between Ri and Kp is −0.58 while the correlation coefficient between Ri and AE/Dst is only −0.29/0.17. The correlation coefficients are local time dependent. Particularly, Ri and Kp are highly correlated (r=−0.72) in the night sector, meaning that the radial distance of IBIPS Ri in the night sector has the good response to the Kp index These observations indicate that Kp plays a key role in determining the position of IBIPS.

scholarly journals Intracluster correlation coefficients in a large cluster randomized vaccine trial in schools: Transmission and impact of shared characteristics

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0254330
Author(s):  
Jane Whelan ◽  
Helen Marshall ◽  
Thomas R. Sullivan
Keyword(s):  
Sample Size ◽  
Rural Areas ◽  
Vaccine Trial ◽  
South Australia ◽  
Correlation Coefficients ◽  
Personal Characteristics ◽  
Future Research ◽  
Intracluster Correlation ◽  
Highly Correlated ◽  
Cluster Randomized

Cluster randomized trials (cRCT) to assess vaccine effectiveness incorporate indirect effects of vaccination, helping to inform vaccination policy. To calculate the sample size for a cRCT, an estimate of the intracluster correlation coefficient (ICC) is required. For infectious diseases, shared characteristics and social mixing behaviours may increase susceptibility and exposure, promote transmission and be a source of clustering. We present ICCs from a school-based cRCT assessing the effectiveness of a meningococcal B vaccine (Bexsero, GlaxoSmithKline) on reducing oropharyngeal carriage of Neisseria meningitidis (Nm) in 34,489 adolescents from 237 schools in South Australia in 2017/2018. We also explore the contribution of shared behaviours and characteristics to these ICCs. The ICC for carriage of disease-causing Nm genogroups (primary outcome) pre-vaccination was 0.004 (95% CI: 0.002, 0.007) and for all Nm was 0.007 (95%CI: 0.004, 0.011). Adjustment for social behaviours and personal characteristics reduced the ICC for carriage of disease-causing and all Nm genogroups by 25% (to 0.003) and 43% (to 0.004), respectively. ICCs are also reported for risk factors here, which may be outcomes in future research. Higher ICCs were observed for susceptibility and/or exposure variables related to Nm carriage (having a cold, spending ≥1 night out socializing or kissing ≥1 person in the previous week). In metropolitan areas, nights out socializing was a highly correlated behaviour. By contrast, smoking was a highly correlated behaviour in rural areas. A practical example to inform future cRCT sample size estimates is provided.

scholarly journals Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests

2017 ◽  
Vol 47 (10) ◽  
Author(s):  
Bruno Giacomini Sari ◽  
Alessandro Dal’Col Lúcio ◽  
Cinthya Souza Santana ◽  
Dionatan Ketzer Krysczun ◽  
André Luís Tischler ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Sample Size ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Fruit Weight ◽  
Pearson Correlation Coefficient ◽  
Cherry Tomato ◽  
Coefficient Of Correlation ◽  
Pearson Coefficient ◽  
Set Up

ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.

AN ASSESSMENT OF THE SDS-SEDIMENTATION TEST FOR THE PREDICTION OF CANADIAN BREAD WHEAT QUALITY

1982 ◽  
Vol 62 (3) ◽  
pp. 545-553 ◽  
Author(s):  
K. R. PRESTON ◽  
P. R. MARCH ◽  
K. H. TIPPLES
Keyword(s):  
Correlation Coefficient ◽  
Bread Wheat ◽  
Sodium Dodecyl ◽  
Correlation Coefficients ◽  
Quality Parameters ◽  
Loaf Volume ◽  
Dough Strength ◽  
Sedimentation Volume ◽  
Highly Correlated ◽  
Wheat Lines

The ability of the sodium dodecyl sulfate (SDS) sedimentation test of Axford et al. (1978) to predict quality characteristics of Canadian bread wheats has been assessed. With appropriate modifications, the test had sufficient "inherent" sensitivity to differentiate Canadian bread wheat lines, obtained from three years of Co-op tests, on the basis of baking quality and physical dough strength. However, the correlation coefficients between SDS-sedimentation volume and the quality parameters tested were highly dependent on environment. Correlation coefficients between SDS-sedimentation volume and Remix loaf volume were strongly affected by protein content with sample sets from the same environment. Sample sets with the lowest average protein contents gave the highest correlations. With combined samples from different environments with protein contents of less than 13.0%, a high correlation coefficient (r = 0.78**) was obtained between SDS-sedimentation volume and Remix loaf volume, whereas with samples of over 14.0% protein the correlation coefficient was insignificant. With sample sets from the same environment, SDS-sedimentation volume was generally highly correlated to farinograph dough development time and extensigraph area.

scholarly journals Phenotypic Correlation of Body Weight and Linear Body Measurements in Muscovy (Cairinia Moschata) and Mallard (Anas Platyrhynchos) Ducks

2020 ◽  
pp. 13-17
Author(s):  
Ologbose F. I. ◽  
Mbara S. W.
Keyword(s):  
Body Weight ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Selection Index ◽  
Body Height ◽  
Correlation Coefficients ◽  
The Body ◽  
Phenotypic Correlation ◽  
Body Measurements ◽  
Linear Body

Data on body weight and linear body measurements (LBMs) namely body height (BH), body length (BL), breast circumference (BC), thigh length (TL), bill length (BiL), wing length (WL) and shank length (SL) were taken from 120 ducks (i. e. 60 Muscovy and 60 Mallard ducks) at 4 and 8 weeks of age were analysed to obtain the phenotypic correlation between LBMs and body weight. The value of the pearson’s linear correlation coefficient to determine the level of relationship between the body weight and linear body measurement. This ranged from 0.488 (SL) – 0.996 (BH) and (0.729 (SL) – 0.996 (Bil) in Muscovy and Mallard duck at week 4 respectively. While, at week 8, the value of the pearson’s linear correlation coefficient ranges from 0.126 (Bil) – 0.960 (BL) and 0.735(BC) – 0.978 (BH) respectively. This positive and mostly significantly phenotypic relationship between the body weight and linear body measurements indicates that an improvement in one trait could leads to an improvement in the other. Correlation coefficients indicate the strength of a linear relation between traits and thus provide useful information about the traits involved for the purpose of breeding and improvement plan. This shows that favourable relationships exist among traits that have higher correlation coefficients, it further explains that such traits could be collectively included in the selection index to achieve positive phenotypic progress.

Sign in / Sign up

Export Citation Format

Share Document