Concurrently Assessing Survey Mode and Sample Size in Off-Site Angler Surveys

REFERENCES

• Baptiste, A. 2016. gridExtra: miscellaneous functions for “Grid” graphics. R package version 2.2.1. R Foundation for Statistical Computing, Vienna. Available: http://cran.r-project.org/package=gridExtra. ( May 2017).
   Google Scholar
• Beardmore, B., L. M. Hunt, W. Haider, M. Dorow, and R. Arlinghaus. 2014. Effectively managing angler satisfaction in recreational fisheries requires understanding the fish species and the anglers. Canadian Journal of Fisheries and Aquatic Sciences 72:500–513.
   Web of Science ®Google Scholar
• Brick, J. M. 2013. Unit nonresponse and weighting adjustments: a critical review. Journal of Official Statistics 29:329–353.
   Web of Science ®Google Scholar
• Buelens, B., and J. A. van den Brakel. 2015. Measurement error calibration in mixed-mode sample surveys. Sociological Methods and Research 44:391–426.
   Web of Science ®Google Scholar
• Callegaro, M., K. L. Manfreda, and V. Vehovar. 2015. Web survey methodology. SAGE Publications, London.
   Google Scholar
• Clottey, T., and W. C. Benton. 2013. Guidelines for improving the power values of statistical tests for nonresponse bias assessment in OM research. Decision Sciences 44:797–812.
   Web of Science ®Google Scholar
• Connelly, N. A., T. L. Brown, and B. A. Knuth. 2000. Assessing the relative importance of recall bias and nonresponse bias and adjusting for those biases in statewide angler surveys. Human Dimensions of Wildlife 5:19–29.
   Google Scholar
• COSEWIC (Committee on the Status of Endangered Wildlife in Canada). 2012. COSEWIC assessment and status report on the White Sturgeon Acipenser transmontanusin Canada. COSEWIC, Gatineau, Quebec.
   Google Scholar
• De Jesus, M. J., S. J. Magnelia, and C. C. Bonds. 2011. Use of a volunteer angler survey for assessing length distribution and seasonal catch trends of trophy Largemouth Bass. North American Journal of Fisheries Management 29:1225–1231.
   Web of Science ®Google Scholar
• De Leeuw, D. 2005. To mix or not to mix data collection modes in surveys. Journal of Official Statistics 21:233–255.
   Google Scholar
• Dillman, D. A., J. D. Smyth, and L. M. Christian. 2014. Internet, phone, mail, and mixed-mode surveys: the tailored design method. Wiley, Hoboken, New Jersey.
   Google Scholar
• Eero, M., H. V. Strehlow, C. M. Adams, and M. Vinther. 2014. Does recreational catch impact the TAC for commercial fisheries? ICES Journal of Marine Science 72:450–457.
   Google Scholar
• Fisher, M. R. 1996. Estimating the effect of nonresponse bias on angler surveys. Transactions of the American Fisheries Society 125:118–126.
   Web of Science ®Google Scholar
• Fisher, M. R. 1997. Segmentation of the angler population by catch preference, participation, and experience: a management-oriented application of recreation specialization. North American Journal of Fisheries Management 17:1–10.
   Google Scholar
• Gigliotti, L., and A. Dietsch. 2014. Does age matter? The influence of age on response rates in a mixed-mode survey. Human Dimensions of Wildlife 19:280–287.
   Google Scholar
• Harrell, F. E. Jr., and with contributions from C. Dupont and many others. 2016. Hmisc: Harrell miscellaneous. R package version 4.0-2. R Foundation for Statistical Computing, Vienna. Available: http://cran.r-project.org/package=Hmisc. ( May 2017).
   Google Scholar
• Hartill, B. W., M. Cryer, J. M. Lyle, E. B. Rees, K. L. Ryan, A. S. Steffe, S. M. Taylor, L. West, and B. S. Wise. 2012. Scale- and context-dependent selection of recreational harvest estimation methods: the Australasian experience. North American Journal of Fisheries Management 32:109–123.
   Web of Science ®Google Scholar
• Hartill, B. W., and C. T. T. Edwards. 2015. Comparison of recreational harvest estimates provided by onsite and offsite surveys: detecting bias and corroborating estimates. Canadian Journal of Fisheries and Aquatic Sciences 72:1379–1389.
   Web of Science ®Google Scholar
• Holt, D., and T. M. F. Smith. 1979. Post stratification. Journal of the Royal Statistical Society Series A (General) 142:33–46.
   Web of Science ®Google Scholar
• Hutt, C. P., and P. W. Bettoli. 2007. Preferences, specialization, and management attitudes of trout anglers fishing in Tennessee tailwaters. North American Journal of Fisheries Management 27:1257–1267.
   Web of Science ®Google Scholar
• Kelley, K. 2007. Sample size planning for the coefficient of variation from the accuracy in parameter estimation approach. Behavior Research Methods 39:755–766.
   PubMed Web of Science ®Google Scholar
• Kelley, K., S. E. Maxwell, and J. R. Rausch. 2003. Obtaining power or obtaining precision: delineating methods of sample-size planning. Evaluation and the Health Professions 26:258–287.
   PubMed Web of Science ®Google Scholar
• Kelley, K., and J. R. Rausch. 2006. Sample size planning for the standardized mean difference: accuracy in parameter estimation via narrow confidence intervals. Psychological Methods 11:363–385.
   PubMed Web of Science ®Google Scholar
• Laborde, L. P., F. C. Rohwer, M. D. Kaller, and L. A. Reynolds. 2014. Surveying Louisiana waterfowl hunters: open web and random mail surveys produce similar responses to attitudinal questions. Wildlife Society Bulletin 38:821–826.
   Web of Science ®Google Scholar
• Landsman, S. J., H. J. Wachelka, C. D. Suski, and S. J. Cooke. 2011. Evaluation of the physiology, behaviour, and survival of adult Muskellunge (Esox masquinongy) captured and released by specialized anglers. Fisheries Research 110:377–386.
   Web of Science ®Google Scholar
• Larkin, M. F., J. S. Ault, R. Humston, and L. Lou. 2010. A mail survey to estimate the fishery dynamics of southern Florida’s Bonefish charter fleet. Fisheries Management and Ecology 17:254–261.
   Web of Science ®Google Scholar
• Lenth, R. V. 2001. Some practical guidelines for effective sample size determination. American Statistician 55:187–193.
   Web of Science ®Google Scholar
• Lewis, E. F., M. Hardy, and B. Snaith. 2013. Estimating the effect of nonresponse bias in a survey of hospital organizations. Evaluation and the Health Professions 36:330–351.
   PubMed Web of Science ®Google Scholar
• Lukacs, P. M. 2007. Development and analysis of joint internet–telephone hunter surveys. Human Dimensions of Wildlife 12:263–273.
   Google Scholar
• Maunder, M. N., and A. E. Punt. 2004. Standardizing catch and effort data: a review of recent approaches. Fisheries Research 70:141–159.
   Web of Science ®Google Scholar
• McCormick, J. L., D. Whitney, D. J. Schill, and M. C. Quist. 2015. Evaluation of angler reporting accuracy in an off-site survey to estimate statewide steelhead harvest. Fisheries Management and Ecology 22:134–142.
   Web of Science ®Google Scholar
• Peress, M. 2010. Correcting for survey nonresponse using variable response propensity. Journal of the American Statistical Association 105:1418–1430.
   Web of Science ®Google Scholar
• Peterman, R. M. 1990. Statistical power analysis can improve fisheries research and management. Canadian Journal of Fisheries and Aquatic Sciences 47:2–15.
   Web of Science ®Google Scholar
• R Development Core Team. 2014. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
   Google Scholar
• Roach, B., J. Trial, and K. Boyle. 1999. Comparing 1994 angler catch and harvest rates from on-site and mail surveys on selected Maine lakes. North American Journal of Fisheries Management 19:203–208.
   Google Scholar
• Ruxton, G. D. 2006. The unequal variance t-test is an underused alternative to Student’s t-test and the Mann–Whitney U-test. Behavioral Ecology 17:688–690.
   Web of Science ®Google Scholar
• Peytchev, A. 2013. Consequences of survey nonresponse. Annals of the American Academy of Political and Social Science 645:88–111.
   Web of Science ®Google Scholar
• Vannieuwenhuyze, J., and G. Loosveldt. 2013. Evaluating relative mode effects in mixed-mode surveys: three methods to disentangle selection and measurement effects. Sociological Methods and Research 42:82–104.
   Web of Science ®Google Scholar
• Vannieuwenhuyze, J., G. Loosveldt, and G. Molenberghs. 2010. A method for evaluating mode effects in mixed-mode surveys. Public Opinion Quarterly 74:1027–1045.
   Web of Science ®Google Scholar
• Vaske, J. J. 2002. Communicating judgments about practical significance: effect size, confidence intervals and odds ratios. Human Dimensions of Wildlife 7:287–300.
   Google Scholar
• Wallen, K. E., A. C. Landon, G. T. Kyle, and M. A. Schuett. 2016. Mode effect and response rate issues in mixed-mode survey research: implications for recreational fisheries management. Fisheries Research 36:852–863.
   Google Scholar
• Walther, B. A., and J. L. Moore. 2005. The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28:815–829.
   Web of Science ®Google Scholar
• Wickham, H. 2009. ggplot2: elegant graphics for data analysis. Available: http://ggplot2.org. ( May 2017).
   Google Scholar
• Wickham, H., and R. Francois. 2016. dplyr: a grammar of data manipulation. R package version 0.5.0. R Foundation for Statistical Computing, Vienna. Available: http://cran.r-project.org/package=dplyr. (May 2017).
   Google Scholar
• Zarauz, L., J. Ruiz, A. Urtizberea, E. Andonegi, E. Mugerza, and I. Artetxe. 2015. Comparing different survey methods to estimate European Sea Bass recreational catches in the Basque Country. ICES Journal of Marine Science 72:1181–1191.
   Web of Science ®Google Scholar
• Zimmerman, D. W. 2012. A note on consistency of non-parametric rank tests and related rank transformations. British Journal of Mathematical and Statistical Psychology 65:122–144.
   PubMed Web of Science ®Google Scholar