(1) Background: Milk is an important product in Mauritania both for livelihood and food and nutritional security. (2) Methods: In this study, we examine the economic performance of cattle farms in the Hodh Chargui region using data from a cross-sectional survey of 50 farms conducted in 2023. (3) Results: The results showed that the most significant cost item was animal feed (54%), followed by labor (40%) and charges induced by health and watering (3% each). In terms of income, the sale of young males accounted for the largest portion (48%), followed by the sales of dry cows (20%), lactating cows (17%), adult males (8%), and milk (7%). The average gross margin was MRU 131,697.82 ± 509,571.84 (equivalent to USD 3300.69 ± 12,771.22) per breeder per year. Out of the farms surveyed, 46% (23/50) reported a positive gross margin, while 54% reported a negative gross margin. (4) Conclusions: These results indicate a wide range of profitability, from lowest to highest, and suggest the need for improved management of cattle farms in Hodh Chargui in order to enhance their economic efficiency.

This article deals with the problematic of self-sufficient development at the theoretical level and in the context of globalization, especially in regard to how the various predominant Western conceptions of such have been understood, analyzed, questioned and/or adapted in the Arab world. The author explores the question of viable development and accumulation in countries emerging from systems of pre-capitalist relations, and attempts to assess whether or not Western expectations and policies – such as those of the World Bank, the International Monetary Fund and the United Nations – are germane to or feasible in such nations and whether or not they facilitate self-reliance or actually impede or militate against it. Taken into consideration are the major theories of exogenous and endogenous growth as well as the impact of international economic and monetary unions in the context of globalization.

The weighted kappa coefficient of a binary diagnostic test is a measure of the beyond-chance agreement between the diagnostic test and the gold standard, and depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the relative importance between the false positives and the false negatives. This article studies the comparison of the weighted kappa coefficients of two binary diagnostic tests subject to a paired design through confidence intervals. Three asymptotic confidence intervals are studied for the difference between the parameters and five other intervals for the ratio. Simulation experiments were carried out to study the coverage probabilities and the average lengths of the intervals, giving some general rules for application. A method is also proposed to calculate the sample size necessary to compare the two weighted kappa coefficients through a confidence interval. A program in R has been written to solve the problem studied and it is available as supplementary material. The results were applied to a real example of the diagnosis of malaria.

Case-control sampling to compare the accuracy of two binary diagnostic tests is frequent in clinical practice. This type of sampling consists of applying the two diagnostic tests to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. In this sampling, the sensitivities are compared from the case sample applying the McNemar’s test, and the specificities from the control sample. Other parameters of binary tests are the positive and negative predictive values. The predictive values of a diagnostic test represent the clinical accuracy of a binary diagnostic test when it is applied to the individuals in a population with a determined disease prevalence. This article studies the comparison of the predictive values of two diagnostic tests subject to a case-control sampling. A global hypothesis test, based on the chi-square distribution, is proposed to compare the predictive values simultaneously. The comparison of the predictive values is also studied individually. The hypothesis tests studied require knowledge of the disease prevalence. Simulation experiments were carried out to study the type I errors and the powers of the hypothesis tests proposed, as well as to study the effect of a misspecification of the prevalence on the asymptotic behavior of the hypothesis tests and on the estimators of the predictive values. The results obtained were applied to a real example on the diagnosis of the Human African Trypanosomiasis. The model proposed was extended to the situation in which there are more than two diagnostic tests.

Positive and negative likelihood ratios are parameters which are used to assess and compare the effectiveness of binary diagnostic tests. Both parameters only depend on the sensitivity and specificity of the diagnostic test and are equivalent to a relative risk. This article studies the comparison of the likelihood ratios of two binary diagnostic tests subject to a paired design through confidence intervals. Six approximate confidence intervals are presented for the ratio of the likelihood ratios, and simulation experiments are carried out to study the coverage probabilities and the average lengths of the intervals considered, and some general rules of application are proposed. A method is also proposed to determine the sample size necessary to estimate the ratio between the likelihood ratios with a determined precision. The results were applied to the diagnosis of coronary artery disease.