[ECOLOG-L] Graduate student position
Folks - as of May 4th, I still have a graduate assistantship that is available for a student interested in investigating the relationship between mosquito community dynamics and risk of disease transmission. Students could start in the Fall or Spring. The position involves collaboration with an interdisciplinary team of researchers that includes ecologists, epidemiologists, mathematicians, and medical entomologists. The successful candidate will have a strong quantitative background and, due to funding limitations, must be a U.S. citizen. Programming experience (R/Matlab/etc.) also is desirable, but an openness to learning is sufficient!. Interested students are encouraged to peruse the TIEHH website (www.tiehh.ttu.edu) and contact me (www.tiehh.ttu.edu/scox) for additional information. Regards Stephen Cox stephen.cox AT ttu.edu
[ECOLOG-L] Ph.D. Assistantship - Ecology of Infectious Disease
Folks - I have a graduate assistantship that is available for a student interested in investigating the relationship between mosquito community dynamics and risk of dengue. The position involves collaboration with an interdisciplinary team of researchers that includes ecologists, epidemiologists, mathematicians, and medical entomologists. The successful candidate will have a strong quantitative background and, due to funding limitations, must be a U.S. citizen. Programming experience also is desirable. Interested students are encouraged to peruse the TIEHH website (www.tiehh.ttu.edu) and contact me (www.tiehh.ttu.edu/scox) for additional information. Regards Stephen Cox myrddin...@gmail.com
[ECOLOG-L] Graduate Assistantships Available
Folks, The Department of Environmental Toxicology and The Institute of Environmental and Human Health (TIEHH), Texas Tech University has up to four positions available for PhD students who are interested in research that lies at the interface of environmental, ecological, and human health sciences. These competitive assistantships offer generous support along with a tuition allowance, with the specific area of research to be determined based on applicant and faculty interest. Of particular interest to ECOLOG, TIEHH has a growing group of faculty and students who are focusing on ecological research that includes investigations of various natural and anthropogenic stressors. Interested students are encouraged to peruse the TIEHH website (www.tiehh.ttu.edu) to find information regarding ongoing research areas. In addition, information regarding the application process can be found at http://www.tiehh.ttu.edu/application_process.html. If you have any questions - please don't hesitate to drop me an email at myrddin...@gmail.com. You can also find my contact info on the TIEHH website. Cheers Stephen Cox _ Stephen B. Cox, Ph. D. Graduate Advisor Department of Environmental Toxicology Institute of Environmental and Human Health Texas Tech University
Re: [ECOLOG-L] Ecology Terms Definition Niche
At one point, I (and some colleagues) were asked to put together a concept map for niche. Here is what we came up with... http://www.tiehh.ttu.edu/scox/niche.html/niche_map.html On Sat, Aug 8, 2009 at 5:51 PM, Wayne Tysonlandr...@cox.net wrote: All: What is your definition of niche? WT
[ECOLOG-L] Graduate Assistantships Available
Folks, The Department of Environmental Toxicology and The Institute of Environmental and Human Health (TIEHH), Texas Tech University has recently acquired additional support for PhD students who are interested in research that lies at the interface of environmental, ecological, and human health sciences. Up to 10 doctoral assistantships will be awarded on a competitive basis, with the specific area of research to be determined based on applicant and faculty interest. Interested students are encouraged to peruse the TIEHH website (www.tiehh.ttu.edu) to find information regarding ongoing research areas. In addition, information regarding the application process can be found at http://www.tiehh.ttu.edu/application_process.html. If you have any questions - please don't hesitate to drop me an email at myrddin...@gmail.com. You can also find my contact info on the TIEHH website. Cheers Stephen Cox _ Stephen B. Cox, Ph. D. Graduate Advisor Department of Environmental Toxicology Institute of Environmental and Human Health Texas Tech University
[ECOLOG-L] PhD Graduate Student Positions
Folks, The Department of Environmental Toxicology and The Institute of Environmental and Human Health (TIEHH), Texas Tech University has openings for PhD students who are interested in research that lies at the interface of environmental, ecological, and human health sciences. Up to five doctoral assistantships will be awarded on a competitive basis, with the specific area of research to be determined based on applicant and faculty interest. Interested students are encouraged to peruse the TIEHH website (www.tiehh.ttu.edu) to find information regarding ongoing research areas. In addition, information regarding the application process can be found at http://www.tiehh.ttu.edu/application_process.html. Established as a joint venture between Texas Tech University and Texas Tech University Health Sciences Center, TIEHH pursues multidisciplinary research in the areas of environmental toxicology and human health. Emphasis is placed on developing innovative approaches to complex research questions that are of current importance, including the areas of biological and chemical threats. Cheers Stephen Cox _ Stephen B. Cox, Ph. D. Graduate Advisor Department of Environmental Toxicology Institute of Environmental and Human Health Texas Tech University
[ECOLOG-L] POSITION ANNOUNCEMENT: Assistant/Associate Professor
Folks - we have just opened a new search for an ecotoxicologist/ecologist who studies the impacts of stressors on ecological systems. Feel free to contact me ([EMAIL PROTECTED]) if you have any questions or would like to discuss the position further. Cheers Stephen Cox *** Faculty Position - Texas Tech University Assistant or Associate Professor The Department of Environmental Toxicology and The Institute of Environmental and Human Health, Texas Tech University is seeking a new Assistant or Associate Professor with expertise in the occurrence and effects of chemical, physical, or biological stressors in the environment. The research focus area of the candidate is open, however, applicants investigating multiple levels of effect and their integration into higher-level impacts are desirable. The candidate will complement and expand areas of expertise represented within our environmental and human health research, teaching, and service programs (see www.tiehh.ttu.edu for program description). The successful applicant will have an established research, publication and funding record, and is expected to maintain an active, externally funded and internationally recognized program. The successful candidate should demonstrate significant evidence of collaborative achievement. In addition, the candidate should excel in teaching and be prepared to contribute to the education and training of graduate students. Applications for this tenured or tenure-track position will be accepted until the position is filled. Applicants must submit online a complete curriculum vitae, statement of teaching philosophy and interests and a self-statement on how the candidate's proposed research will compliment the current expertise of the department and institute. For a confidential discussion of the position, contact Stephen Cox at [EMAIL PROTECTED] For further details on the application process and submittal of online materials, access the TTU Employment website at http://jobs.texastech.edu and reference Requisition Number 76844. Established as a joint venture between Texas Tech University and Texas Tech University Health Sciences Center, TIEHH pursues multidisciplinary research in the areas of environmental toxicology and human health. Emphasis is placed on developing innovative approaches to complex research questions that are of current importance, including the areas of biological and chemical threats. Information on the city of Lubbock, Texas can be found at www.visitlubbock.org and information about Texas Tech University can be found by visiting www.ttu.edu Female and minority candidates are strongly encouraged to apply. TTU is an Equal Opportunity/Affirmative Action Institution and actively seeks diversity among its employees. Furthermore, TTU is sensitive to the needs of dual career couples.
Re: [ECOLOG-L] Good theoretical ecology book.
Roughgarden's Primer of Ecological Theory deserves some mention here. (BTW, it is Matlab based.) On Tue, Feb 19, 2008 at 3:35 PM, Ted Hart [EMAIL PROTECTED] wrote: Hello ecologgers. I'm curious if anyone had any opinions on a good theoretical ecology books out there. One I've come across is Ted Case's 2000 book An Illustrated Guide to Theoretical Ecology. But before I spend $60 I thought I'd ask around. Looking for something relatively accessible to an ecologist with a mathematical bend, but not much formal training in math. So something like May's seminal book is a bit over my head. Thanks for any input. Cheers, Ted
[ECOLOG-L] Faculty Position
Ecology/Environmental Toxicology Faculty Position The Department of Environmental Toxicology and The Institute of Environmental and Human Health, Texas Tech University is seeking a new faculty member at the associate or full professor level, however all qualified applicants, at all ranks with expertise in the occurrence and effects of chemical, physical or biological stressors in the environment will be considered. The research focus area of the candidate is open, however, applicants investigating multiple levels of effects and their integration into higher-level impacts are desirable. The candidate will complement and expand areas of expertise represented within our environmental and human health research, teaching, and service programs (see www.tiehh.ttu.edu for program description). The successful applicant will have an established research, publication and funding record, and is expected to maintain an active, externally funded and internationally recognized program. The successful candidate should demonstrate significant evidence of collaborative achievement. The ideal candidate should also excel in teaching and be prepared to contribute to the education and training of graduate students. Applications for this tenured or tenure-track position will be accepted until the position is filled. Applicants must submit online a complete curriculum vitae, statement of teaching philosophy and interests and a self-statement on how the candidate's proposed research will compliment the current expertise of the department and institute. For a confidential discussion of the position, contact Ernest E. Smith at 806-885-0233. For further details on the application process and submittal of online materials, access the TTU Employment website at http://jobs.texastech.edu and reference Requisition Number 74859. Established as a joint venture between Texas Tech University and Texas Tech University Health Sciences Center, TIEHH pursues multidisciplinary research in the areas of environmental toxicology and human health. Emphasis is placed on developing innovative approaches to complex research questions that are of current importance, including the areas of biological and chemical threats. Female and minority candidates are strongly encouraged to apply. TTU is an Equal Opportunity/Affirmative Action Institution and actively seeks diversity among its employees.
Faculty position - Texas Tech University
The Department of Environmental Toxicology/Institute of Environmental and Human Health, Texas Tech University is seeking a new faculty member at the associate or full professor level with a focus on ecologically and or environmentally related diseases. The candidate will complement and expand areas of expertise represented within our environmental and human health research, teaching, and service programs (see www.tiehh.ttu.edu for program description). The successful applicant will have a Ph.D., an outstanding research, publication and funding record, and is expected to build an active externally funded and internationally recognized program. The successful candidate should exhibit significant evidence of internal and external collaborative achievement. The ideal candidate should also be able to demonstrate excellence in teaching and be prepared to contribute to the education and training of graduate students. Applications for this tenured or tenure-track position will be accepted until the position is filled. Applicants must submit online a complete curriculum vitae, statement of teaching philosophy and interests and a self-statement on how the candidate's proposed research will compliment the current expertise of the department and institute (including start-up requirements with Annotated Budget). Please process your application by accessing the Employment site at http://jobs.texastech.edu to reference Requisition Number 74859. Applicants should provide names and contact information for three colleagues willing to provide confidential letters of recommendation on their behalf. Letters of recommendations should be emailed to [EMAIL PROTECTED] Established as a joint venture between Texas Tech University and Texas Tech University Health Sciences Center, TIEHH pursues multidisciplinary research in the areas of environmental toxicology and human health. Emphasis is placed on developing innovative approaches to complex research questions that are of current importance, including the areas of biological and chemical threats. Female and minority candidates are strongly encouraged to apply. TTU is Equal Opportunity/Affirmative Action Institution and Actively seeks diversity among its employees. * Stephen B. Cox [EMAIL PROTECTED]
Re: nonparametric repeated measures
Hi Lucy - although I would recommend a mixed model for a variety of reasons (in particular, you can model heteroscedasticity), it does still assume normality. So, the mixed model does not necessarily solve issues of nonparametric data (I think you mean nonnormal). As I see it, you have a couple of options ... a) if your data are well-balanced, there is literature that suggests that most ANOVA related analyses perform relatively well despite non-normal errors. b) analyze rank-transformed data, but there can still be issues here (especially if you have a lot of 'ties'). You can also do a mixed model on ranks, but you have to be aware of, and model, the effects that rank transformations can have on variances. You could also look into bootstrap approaches for repeated measures data, but I don't recall much about this off the top of my head. Opinions vary considerably on this topic - (FWIW, I would tend to go with option a) - but much of the decision depends on the details of your data. Stephen On 4/23/07, Lucy [EMAIL PROTECTED] wrote: I'm working with some percent cover data from plots that have been measured annually for the past five years. In several plots and during some years there is little to no vegetation coverage, so the data are heavily skewed; the common transformations (log, square root) haven't worked. Is there a way to do repeated measures analyses on non-normal data? Is PROC MIXED robust enough to handle nonparametric data? Thanks for your help! Lucy
Re: nonparametric repeated measures
Yes - this alleviates the assumption of normality (although I am not sure if I would classify % cover as binomial/logit). This biggest hurdle for generalized mixed (or the usual mixed models) for Lucy, though, is how to generate tests of her main effects. I don't know what SAS is doing these days, but there really is no consensus on how to test for treatment effects outside of interpretation of model parameters. (e.g., there has been a bit of discussion on this related to the new R library 'lmer' for doing mixed effects models) On 4/24/07, Bahram Momen [EMAIL PROTECTED] wrote: The best option in SAS is using 'PROC GLIMMIX' and define an appropriate 'DISTribution' and a related 'LINK' function. Bahram Momen Environmental Science Statistics 1108 H.J. Patterson Hall Environmental Science Technology Dept. University of Maryland College Park, MD 20742 301 405 1332, [EMAIL PROTECTED] Stephen B. Cox wrote: Hi Lucy - although I would recommend a mixed model for a variety of reasons (in particular, you can model heteroscedasticity), it does still assume normality. So, the mixed model does not necessarily solve issues of nonparametric data (I think you mean nonnormal). As I see it, you have a couple of options ... a) if your data are well-balanced, there is literature that suggests that most ANOVA related analyses perform relatively well despite non-normal errors. b) analyze rank-transformed data, but there can still be issues here (especially if you have a lot of 'ties'). You can also do a mixed model on ranks, but you have to be aware of, and model, the effects that rank transformations can have on variances. You could also look into bootstrap approaches for repeated measures data, but I don't recall much about this off the top of my head. Opinions vary considerably on this topic - (FWIW, I would tend to go with option a) - but much of the decision depends on the details of your data. Stephen On 4/23/07, Lucy [EMAIL PROTECTED] wrote: I'm working with some percent cover data from plots that have been measured annually for the past five years. In several plots and during some years there is little to no vegetation coverage, so the data are heavily skewed; the common transformations (log, square root) haven't worked. Is there a way to do repeated measures analyses on non-normal data? Is PROC MIXED robust enough to handle nonparametric data? Thanks for your help! Lucy
Re: Question about random sampling
Ophelia - very easy to implement in R/S-plus (check out the function 'sample' in R ) but, to be able to answer your question about other methods - what, exactly, are you trying to do? get CI's, etc? On 4/11/07, Ophelia Wang [EMAIL PROTECTED] wrote: Hi, I have a data set that has about 15,000 data points (rows) that document values of 15 variables (columns). Now I'd like to perform a random sampling process (run 10,000 times) to randomly select 470 points and get the mean values of my 15 variables (columns) out of these 470 points after the 10,000 times of random sampling. Can anyone tell me how to write a script in SAS, SYSTAT, R or S-Plus to perform this analysis? Or are there other methods I can use? Thanks a lot! Ophelia -- Ophelia Wang Doctoral student Department of Geography and Environment University of Texas at Austin 210 West 24th Street, Austin, TX 78712, USA Phone: 1-512-471-5116 Fax: 1-512-471-5049 Email: [EMAIL PROTECTED]
Re: Dealing with non-normal, ordinal data for 2-way ANOVA with interactions
Well - opinions vary on this topic, but, a couple of things to consider in 2-way factorial ANOVA with a non-normal response. 1) ANOVA is robust with respect to deviations from normality, especially with decent sample sizes. (Good ole Central Limit Theorem comes in handy!) So, what is your sample size in each cell of the analysis? You may be worrying over a non-issue :) 2) you can always just rank-transform the data and run the 2-way ANOVA on ranks. This may have some problems... (see Seaman et al. 1994 TREE 9: 261-263). I am generally of the opinion that folks tend to worry a bit too much about normality in an ANOVA context (and Mixed models can deal with heterscedasticity which is more of a problem)... but others disagree. It would probably be worth your while to actually examine the distributions of residuals in each cell and get a better idea of what they do look like. On 3/7/07, Ryan Earley [EMAIL PROTECTED] wrote: Help with stubbornly non-normal data We have a data set with 2 independent variables and 1 dependent (Gosner stage for amphibian larvae). We have tried every creative way to transform the data and end up with significant deviation from normality each time. What we'd like to ultimately do is test both main effects and their interaction (which effectively eliminates the use of two Kruskal-Wallis tests or Friedman's two-way ANOVA). We would be indebted to anyone who might have a suggestion on how to proceed statistically. Thanks for your help in advance. Best, Ryan L. Earley Foung Vang Cal State Fresno
Re: Spatial analysis
Craig - checking for clumped vs. random spatial patterns can be as easy as comparing observed distributions of the number of individuals among locations against a poisson pdf. However, a 10 x 10m grid is, in my opinion, a bit small to be trying to make any decisions about spatial patterns... perhaps you could provide more details on your design. Stephen On 12/21/06, Craig Streatfeild [EMAIL PROTECTED] wrote: Hello all, I need some advice on analyzing spatial patterns. I have been trapping small mammals on a 10m x 10m grid and want to analyze the spatial pattern (clumped or random) of 1) all individuals, 2) adults only and 3) males and females separately. I also measured several ecological variables at each grid point to determine if individuals were associating with certain variables. There seems to be numerous methods out there across a vast amount of literature which can become a little confusing. Hence, I would really appreciate some advice on what people think are the 'best' methods that are currently in use to analyze spatial patterns. Cheers, Craig
Re: Biostatistics texts
Hi Mark - I have used Zar in an introductory course for several years. It is very good text at balancing breadth and depth. That said, if I was starting over - especially for students with the ecological/field biology focus you mentioned - I would seriously consider the Quinn and Keough text that was suggested. This is a fantastic book! Take a look at both and see which fits the topics you wish to cover in the manner in which you would like to present them. On 10/18/06, Dixon, Mark [EMAIL PROTECTED] wrote: Does anyone have recommendations for a text for introductory biostatistics? The class is junior/senior level course with mostly students with an ecological/ environmental bent, although there may be some pre-meds as well. From my discussions with others, Zar seems to be the top choice, but I was wondering about other possible contenders (as well as any feedback folks have on Zar). Any input would be most appreciated. Mark D. Dixon Assistant Professor Department of Biology University of South Dakota Vermillion, SD 57069 Phone: (605) 677-6567 Fax: (605) 677-6557 Email: [EMAIL PROTECTED]
Re: Important MATLAB books for Ecologists
Roughgarden's book is great - also check out Matrix Population Models by Caswell for THE reference in matrix-based pop models. On 9/13/06, krishna prasad [EMAIL PROTECTED] wrote: Dear all, I am looking for important books / literature on MATLAB (that use ecological examples) specifically designed for ecologists. Greatly appreciate your suggestions on the above. Sincerely, Krishna Dr. Krishna Prasad Vadrevu Research Scientist 201 Thorne Hall, Agroecosystem Management Program 1680 Madison Avenue, The Ohio State University Wooster, OHIO, 44691-4096, USA Fax : 330-263-3686 Phone : 330-202-3539 Email : [EMAIL PROTECTED] - Do you Yahoo!? Get on board. You're invited to try the new Yahoo! Mail.
Re: standard deviation of a slope
Hi Geoff - just have a quick minute.. so, I'll hazard a response without thinking about it too much :) On 8/16/06, Geoffrey Poole [EMAIL PROTECTED] wrote: Doesn't sqrt(SSx) increase with n? If so, won't the standard error of the slope decrease with increasing sample size?? Yes - the standard error of the slope will decrease with increasing sample size. I realize SE of estimate and SE of slope do not represent the same thing, statistically, but by comparing the SE of estimate across regressions of the same X and Y variables from different environments, couldn't one assess the expected accuracy of resulting predictions across environments using data sets with different sample size? I think this is what Sarah is looking for... Well - (again, not having thought about this much!) if I wanted to assess the accuracy of predictions, I would take a look at the prediction bands of the regression lines. But, all of these things (SE estimate, prediction intervals, R^2, etc.) are all related measures of the accuracy of a regression. I suspect that what Zar is referring to here is that the standard error of the estimate is in the same units as the dependent variable. Hence, you can divide it by the mean to get a unitless measure. If your suspicion is true, why would Zar have continued on to say ... making the examination of [the SE of estimate] a poor method for comparing regressions (page 335, fourth edition). Why would a unit-ed (i.e. non-unitless) measure automatically be poor for comparing regressions? The continuation of the statement would make a lot more sense to me if Zar really were talking about instances where SE of estimate were proportional to the magnitude of the dependent variable. I read Zar's comment (a unitless measure) (p335) as a reminder that you would want to correct for any effect of the magnitude of Y by dividing the SE of estimate (not residual variance) by the mean to avoid mixed units... Also, what would be the point of dividing by the mean Y if not to remove an effect of increasing magnitude of Y? Is there another compelling reason to do this? Well - the only reason I can think of is to avoid mixed units - as you pointed out. It's the same basic principle of using a coefficient of variation. Perhaps a better characterization of the relationship between the SE of the estimate and the magnitude of Y is that, the SE of the estimate TENDS to be proportinal to the magnitude of the dependent variable. That is - although it is not necessarily so (as in adding a constant to all values), observations with a larger mean tend to have a larger variance than observations with a smaller mean, as in your example of weights. I'd appreciate your thoughts... Thanks, -Geoff
Re: Testing regression slopes for difference
Your approach is valid ONLY IF you are willing to ignore the fact that the slope to which you are comparing your slope is itself an estimate. That is - you can use your CI to compare to a particular hypothesized value - basically testing the hypothesis Ho: beta = beta_0, where beta_0 is some hypothesized value, possibly from the literature. However, if you really want to see if two slopes are equal, say Ho: beta_1 = beta_2, you are better off using the test on p. 360 of Zar. This essentially looks at the CI of the difference in slopes (b_1 - b_2) to see if it includes 0. On 8/16/06, David Whitacre [EMAIL PROTECTED] wrote: While we're on regression--I know this is a really dumb question and I should know the answer. But here goes, my ignorance on display: In comparing some regressions to published ones, how do I test for significant difference in slope? I have calculated the 95% C.I. of my slope by using the t distribution applied to the SE of the slope, as described on p. 331 of Zar (1996, 3rd edition). If somebody else's slope is outside of this C.I., are the two slopes significantly different at p = 0.05? That is, I don't have to consider the C.I. on their slope? Thanks much for any enlightenment on this very basic issue. Dave W.
Re: standard deviation of a slope
On 8/16/06, David Bryant [EMAIL PROTECTED] wrote: Bob, I have a similar question to Sarah's and it may even be the same; I'm using orthogonal regression to determine the equivalence of two variables, both with errors. I want to use the S.E. of the slope to compare to the optimum slope of one (equivalence among variable responses). I contacted JMP (SAS institute) and they recommend the two-one-sided test (TOST) which I understand as simply increasing the alpha to 0.10. But this still gives a very large confidence interval providing a less than robust test. In some instances a slope of 2 is not significantly different than slope of 1. (!!??) In fact I have not found one instance in which the slopes differ. This seems like a universal type II error to me. Can I use the standard test of homogeneity of slopes used in ANCOVA and compare to 1 (s.e. =3D0) or would that lead to a type I error? I would just look at the CI for your slope estimate and see if it included 1. Thanks for your time, David David M Bryant Ph D University of New Hampshire Environmental Education Program Durham, NH 03824 [EMAIL PROTECTED] 978-356-1928 On Aug 16, 2006, at 9:39 AM, Anon. wrote: Sarah Gilman wrote: Is it possible to calculate the standard deviation of the slope of a regression line and does anyone know how? My best guess after reading several stats books is that the standard deviation and the standard error of the slope are different names for the same thing. Technically, the standard error is the standard deviation of the sampling distribution of a statistic, so it is the same as the standard deviation. So, you're right. The context of this question is a manuscript comparing the usefulness of regression to estimate the slope of a relationship under different environmental conditions. A reviewer suggested presenting the standard deviation of the slope rather than the standard error to compare the precision of the regression under different conditions. For unrelated reasons, the sample sizes used in the compared regressions vary from 10 to 200. The reviewer argues that the sample size differences are influencing the standard error values, and so the standard deviation (which according to the reviewer doesn't incorporate the sample size) would be a more robust comparison of the precision of the slope estimate among these different regressions. Well of course the sample sizes differences are influencing the standard error values! And so they should: if you have a larger sample size, then the estimates are more accurate. Why would one want anything other than this to be the case? In some cases, standard errors are calculated by dividing a standard deviation by sqrt(n), but these are only special cases. It may be that the reviewer can provide further enlightenment, but from what you've written, I'm not convinced that they have the right idea. Bob -- Bob O'Hara Dept. of Mathematics and Statistics P.O. Box 68 (Gustaf H=84llstrmin katu 2b) FIN-00014 University of Helsinki Finland Telephone: +358-9-191 51479 Mobile: +358 50 599 0540 Fax: +358-9-191 51400 WWW: http://www.RNI.Helsinki.FI/~boh/ Journal of Negative Results - EEB: http://www.jnr-eeb.org
