from setting the partial derivatives of the log-likelihood functions equal to 0. Convergence criteria are used to determine when the iterations cease. For example, the criterion might be that the mean item estimate changes by less than a certain value, such as 0.001, between one iteration and another for all items. See also Expectation-maximization algorithm Rasch model References Linacre, J.M. (2004). Estimation methods for Rasch measures. Chapter 2 in E.V. Smith & R. M. Smith (Eds.) Introduction to Rasch Measurement. Maple Grove MN: JAM Press. Linacre, J.M. (2004). Rasch model estimation: further topics. Chapter 24 in E.V. Smith & R. M. Smith (Eds.) Introduction to Rasch Measurement. Maple Grove MN: JAM Press. von Davier M., Rost J. (1995) Polytomous Mixed Rasch Models. In: Fischer G.H., Molenaar I.W. (eds) Rasch Models. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4230-7_20 von Davier, M. (2016). The Rasch Model. Chapter 3 in: van der Linden, W. (ed.) Handbook of Item Response Theory, Vol. 1. Second Edition. CRC Press, p. 31-48. https://www.taylorfrancis.com/chapters/edit/10.1201/9781315374512-12/rasch-model-matthias-von-davier Psychometrics Maximum likelihood estimation