Annotated bibliographyThis collection of references, divided into 3 subject fields, provides additional reading to the subject sample designs.
1. Technical reference books on sample surveys
Beginners� level explaination of the sampling methods associated with the inventory of forest resources. It avoids extensive coverage of theoretical statistics and mathematics in favor of thorough coverage of forest inventory topics for the practitioner. Not available on-line. Hardcopy is available at mentioned url.
This reference text as one of several seminal publications in sample surveys of finite populations. The first chapter has excellent advice on the design of sample surveys. It clearly demonstrates a wide range of sampling methods now in use by governments, in business, market and operations research, social science, medicine, public health, agriculture, and accounting. It gives proofs of all the theoretical results used in modern sampling practice. Chapters include Simple Random Sampling; Sampling for Proportions and Percentages; The Estimation of Sample Size; Stratified Random Sampling; Further Aspects of Stratified Sampling; Ratio Estimators; Regression Estimates; Systematic Sampling; Single-Stage Cluster Sampling: Clusters of Equal Sizes; Single-Stage Cluster Sampling: Clusters of Unequal Sizes; Subsampling with Units of Equal Size; Subsampling with Units of Unequal Sizes; Double Sampling; and Sources of Error in Surveys.
Classic text on forest sampling with cluster plots, including variance estimates in presence of spatial autocorrelation
Classic text writtenm, in part, by former the Director of the Statistics Division at the Food and Agricultural Organization of the United Nations. Strong in agricultural applications. Not available on-line. Hardcopy is available at metioned url.
Featuring the model assisted approach to estimation in surveys; this book stresses important general principles for estimation and analysis in surveys. Chapter 1 covers the basics of designing a sample survey. The book includes the use of modelling in sampling, stating the precision in survey estimates, use of supplementary information, e.g. from census or administrative files, nonresponse and missing data, regression and other types of statistical analysis of survey data, survey errors and error models, and estimation for subpopulations and small areas. Intended for statistics students, survey methodologists and those engaged in survey research in a variety of disciplines. Not available on-line. Hardcopy is available at mentioned url.
Designed to aid readers in gathering the most reliable quantitative information on forests for the least cost. Thoroughly explains the interrelationships between sampling strategies; discusses forestry techniques of efficient tactics; examines new developments in statistics having immediate applications in forestry and describes related developments that should have relevance in the future. Includes practical methods for dealing with forest data such as tree number, height, diameter and marketable wood. Chapters include: Focus, Fundamental Concepts, and Theory; Probabilistic Sampling Strategies; Forest Sampling--Single Level; Multi-Information Sources for Sampling; Model-Based Inference; Mensurational Aspects of Forest Inventory; and Future Directions in Multiresource Sampling in Forestry. Not available on-line. Hardcopy is available at metioned url.
This text presents the statistical theory of inventory and monitoring from a probabilistic point of view. It is a free, popular version of the 1993 text by Schreuder, Gregoire and Wood (S.N. 1002). It starts with the basics and shows the interrelationships between designs and estimators. It includes useful open source software. Various sources of ancillary information are described and applications of the sampling strategies are discussed. Classical and bootstrap variance estimators are discussed also. Numerous problems with solutions are given, often based on the experiences of the authors. Key additional references are cited as needed or desired.
Provides an up-to-date treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. Covers methods that combine design and model-based approaches, adjusting for nonsampling errors, and the use of link-tracing designs. It covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio estimators and regression estimation; sufficient data, model, and design in practical sampling; useful designs such as stratified, cluster and systematic, multistage, double and network sampling; detectability methods for elusive populations; spatial sampling; and adaptive sampling designs. Not available on-line. Hardcopy is available mentioned url.