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Jack C. Kiefer; Lawrence D. Brown; Ingram Olkin; Jerome Sacks; Henry P. Wynn Springer-Verlag New York Inc. (2011) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Jean Dickinson Gibbons; Ingram Olkin; Milton Sobel Society for Industrial & Applied Mathematics,U.S. (1987) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Jack Carl Kiefer; Lawrence D. Brown; Ingram Olkin; Jerome Sacks; Henry P. Wynn Springer-Verlag New York Inc. (1986) Saatavuus: Loppuunmyyty Kovakantinen kirja
Jack Carl Kiefer; Lawrence Brown; Ingram Olkin; Jerome Sacks; Henry P. Wynn Springer-Verlag New York Inc. (2012) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Jack Carl Kiefer; Lawrence Brown; Ingram Olkin; Jerome Sacks; Henry P. Wynn Springer-Verlag New York Inc. (2015) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Jack Carl Kiefer; Lawrence D Brown; Ingram Olkin; Jerome Sacks; Henry P. Wynn Springer-Verlag New York Inc. (2015) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Jack Carl Kiefer; Lawrence Brown; Ingram Olkin; Jerome Sacks; Henry P. Wynn Springer-Verlag New York Inc. (2015) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Jack Carl Kiefer; Lawrence D. Brown; Ingram Olkin; Jerome Sacks; Henry P. Wynn Springer-Verlag New York Inc. (2016) Saatavuus: Tilaustuote Pehmeäkantinen kirja
The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader. Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.
