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Strength of the Relationship 143 Correlation coefficients do not buy generic baycip 500 mg on line, however discount baycip 500mg, measure in units of “consistency cheap 500mg baycip with amex. Instead, we evaluate any correlation coefficient by comparing it to the extreme values of 0 and ;1. Perfect Association A correlation coefficient of 11 or 21 describes a perfectly consistent linear relationship. Other data having the same correlation coefficient produce similar patterns, so we envision similar scatterplots. A coefficient of ;1 indicates that everyone who obtains a particular X score obtains one and only one value of Y. Second, and conversely, the coefficient communicates the variability in the Y scores paired with an X. When the coefficient is ;1, only one Y is paired with an X, so there is no variability—no differences—among the Y scores paired with each X. Third, the coefficient communicates how closely the scatterplot fits the regression line. And, because it is a perfect straight-line relationship, all data points will lie on the regression line. Fourth, the coefficient communicates the relative accuracy of our predictions when we predict participants’ Y scores by using their X scores. A coefficient of ;1 indicates perfect accuracy in predictions: because only one Y score occurs with each X we will know every participants’ Y score every time. Note: In statistical lingo, because we can perfectly predict the Y scores here, we would say that these X variables are perfect “predictors” of Y. Further, recall from Chapter 5 that the variance is a way to measure differences among scores. When we can accurately predict when different Y scores will occur, we say we are “accounting for the variance in Y. To communicate the perfect accuracy in predictions with correlations of ;1, we would say that “100% of the variance is accounted for. Intermediate Association A correlation coefficient that does not equal ;1 indicates that the data form a linear relationship to only some degree. The closer the coefficient is to ;1, however, the closer the data are to forming a perfect relationship, and the closer the scatterplot is to forming a straight line. Therefore, the way to interpret any other value of the correla- tion coefficient is to compare it to ;1. First, consistency: A coefficient less than ;1 indicates that not every participant at a particular X had the same Y. That is, even though different values of Y occur with the same X, the Y scores are relatively close to each other. Second, variability: By indicating reduced consistency, this coefficient indicates that there is now variability (differences) among the Y scores at each X. Third, the scatterplot: Because there is variability in the Ys at each X, not all data points fall on the regression line. Fourth, predictions: When the correlation coefficient is not ;1, knowing partici- pants’ X scores allows us to predict only around what their Y score will be. This indicates that our predicted Y scores will be close to the actual Y scores that participants obtained, and so our error will be small. With predictions that are close to participants’ Y scores, we would describe this X variable as “a good predictor of Y. The key to understanding the strength of any relationship is this: As the variability—differences—in the Y scores paired with an X becomes larger, the relationship becomes weaker. The correlation coefficient communicates this because, as the variability in the Ys at each X becomes larger, the value of the correlation coefficient approaches 0. First, instead of seeing a different Y scores at different Xs, we see very different Ys for individuals who have the same X. Second, instead of seeing one value of Y at only one X, the Y scores at different Xs overlap, so we see one value of pairedY with different values of X. Thus, the weaker the relationship, the more the Y scores tend to change when X does not, and the more the Y scores tend to stay the same when X does change. Thus, it is the variability in Y at each X that determines the consistency of a relation- ship, which in turn determines the characteristics we’ve examined. Instead, our prediction errors will be large because we have only a very general idea of when higher Y scores tend to occur and when lower Y scores occur. Thus, this X is a rather poor “predictor” because it “accounts” for little of the variance among Y scores. Zero Association The lowest possible value of the correlation coefficient is 0, indicating that no relation- ship is present. When no rela- tionship is present, the scatterplot is circular or forms an ellipse that is parallel to the X axis. A scatterplot like this is as far from forming a slanted straight line as possible, and a correlation coefficient of 0 is as far from ;1 as possible. Therefore, this coefficient tells us that no Y score tends to be consistently associated with only one value of X. Instead, the Ys found at one X are virtually the same as those found at any other X. This also means that knowing someone’s X score will not in any way help us to predict the corre- sponding Y. In a ______ relationship, as the X scores increase, negative linear relationship, the Y scores tend to the Y scores increase or decrease only. The more that you smoke cigarettes, the lower consistently one Y occurs with one X, the is your healthiness. This is a ______ linear smaller the variability in Ys at an X, the more relationship, producing a scatterplot that slants accurate our predictions, and the narrower the ______ as X increases. In a stronger relationship the variability among the shows little variability in Y scores; (3) by knowing an Y scores at each X is ______, producing a scatter- individual’s X, we can closely predict his/her Y score; plot that forms a ______ ellipse. However, statisticians have developed a number of correlation coefficients having dif- ferent names and formulas.

Individual scores always differ much more than their means buy baycip 500 mg with mastercard, but this still provides a frame of reference cheap 500mg baycip. For example discount baycip 500 mg visa, if individual scores differ by an “average” of 20, then we know that many large differences among scores occur in this situation. Therefore, a difference of 3 between two samples of such scores is not all that impres- sive. Because smaller differ- ences occur in this situation, a difference between conditions of 3 is more impressive. Thus, we standardize the difference between our sample means by comparing it to the population standard deviation. This is the logic behind the measure of effect size known as Cohen’s d: It measures effect size as the magnitude of the difference between the conditions, relative to the population standard deviation. The formulas for Cohen’s d are: Independent-samples t-test Related-samples t-test X1 2 X2 D d 5 d 5 s2 s2 3 pool 3 D For the independent-samples t-test, the difference between the conditions is meas- ured as X1 2 X2 and the standard deviation comes from the square root of the pooled variance. For the related-samples t-test, the difference between the conditions is measured by D and the standard deviation comes from finding the square root of the estimated vari- ance 1s2. First, the larger the absolute size of d, the larger the impact of the independent variable. In fact, Cohen1 proposed the following interpretations when d is the neighborhood of the following amounts: Values of d Interpretation of Effect Size d 5. Second, we can compare the relative size of different ds to determine the relative impact of a variable. Others think of d as the amount of impact the independent variable has, which can- not be negative. Effect Size Using Proportion of Variance Accounted For This approach measures effect size, not in terms of the size of the changes in scores but in terms of how consistently the scores change. Here, a variable has a greater impact, the more it “causes” everyone to behave in the same way, producing virtually the same score for everyone in a particular condition. This then is an important variable, because by itself, it pretty much controls the score (and behavior) that everyone exhibits. Thus, in an experiment, the proportion of variance accounted for is the pro- portional improvement achieved when we use the mean of a condition as the predicted score of participants tested in that condition compared to when we do not use this approach. Put simply it is the extent to which individual scores in each con- dition are close to the mean of the condition, so if we predict the mean for someone, we are close to his or her actual score. When the independent variable has more con- trol of a behavior, everyone in a condition will score more consistently. Then scores will be closer to the mean, so we will have a greater improvement in accurately pre- dicting the scores, producing a larger proportion of variance accounted for. On the other hand, when the variable produces very different, inconsistent scores in each condition, our ability to predict them is not improved by much, and so little of the variance will be accounted for. In Chapter 8, we saw that the computations for the proportion of variance accounted for are performed by computing the squared correlation coefficient. For the two-sample experiment, we compute a new correlation coefficient and then square it. The squared point-biserial correlation coefficient indicates the propor- tion of variance accounted for in a two-sample experiment. This pb can produce a proportion as a low as 0 (when the variable has no effect) to as high as 1. In real research, however, a variable typically accounts for between about 10% and 30% of the variance, with more than 30% being a very substantial amount. Statistics in Published Research: The Two-Sample Experiment 283 The formula for computing r2 is pb 1t 22 2 obt rpb 5 2 1tobt2 1 df This formula is used with either the independent-samples or related-samples t-test. Then, for independent samples, df 5 1n1 2 12 1 1n2 2 12 For related samples, df 5 N 2 1. Hypnosis is not of major importance here, because scores are not consis- tently very close to the mean in each condition. Therefore, hypnosis is only one of a number of variables that play a role here, and, thus, it is only somewhat important in determining recall. Further, fewer other variables need to be considered in order to completely predict scores, so this is an important relationship for understanding phobias and the therapy. We also use the proportion of variance accounted for to compare the relationships from different studies. Thus, the role of therapy in determining fear scores (at 67%) is about three times larger than the role of hypnosis in determining recall scores (which was only 22%). Thus, a published report of our independent-samples hypnosis study might say, “The hypnosis group (M 5 23. Obviously, you perform the independent-samples t-test if you’ve cre- ated two independent samples and the related-samples t-test if you’ve created two related samples. In both procedures, if tobt is not significant, consider whether you have sufficient power. If tobt is significant, then focus on the means from each condition so that you summarize the typical score—and typical behavior—found in each condition. Use effect size to gauge how big a role the independent variable plays in determining the behaviors. Finally, interpret the relationship in terms of the underlying behaviors and causes that it reflects. For either, the program indicates the at which tobt is significant, but for a two-tailed test only. It also computes the descriptive statistics for each condition and automatically computes the confidence interval for either 1 2 2 or D. Two samples are independent when participants are randomly selected for each, without regard to who else has been selected, and each participant is in only one condition. The independent-samples t-test requires (a) two independent samples, (b) normally distributed interval or ratio scores, and (c) homogeneous variance. Homogeneity of variance means that the variances in the populations being represented are equal.

Auditory hair cell replacement and hearing improvement by Atoh1 gene therapy in deaf mammals discount 500mg baycip mastercard. Rapid recovery from acoustic trauma: chicken soup order 500mg baycip, potato knish buy 500mg baycip otc, or drug interaction? Shearing motion in the hearing organ measured by confocal laser heterodyne interferom- etry. Structure of the stereocilia side links and mor- action with internet-based data collection interface, genotyping with phology of auditory hair bundle in relation to noise exposure in proteomics, data mining and evaluation with artiﬁcial intelligence-based the chinchilla. Intensity-dependent changes in oxygenation of cochlear perilymph during acoustic exposure. This site-speciﬁc response might be in the development of the vertebrate inner ear. Apoptosis 2004; explained by the different structure of the blood–labyrinth barrier 9(3):255–264. Successful treatment of noise-induced References cochlear ischemia, hypoxia, and hearing loss. The effect of blood ﬂow promoting drugs on of outer hair cell apoptosis in the chinchilla cochlea following cochlear blood ﬂow, perilymphatic pO(2) and auditory function exposure to impulse noise. Biochemical pathways of caspase activation role in oxidative stress-induced apoptosis of inner ear sensory during apoptosis. Proliferation of functional perform distinct, non-redundant roles during the demolition hair cells in vivo in the absence of the retinoblastoma protein. F-actin cleavage in apop- porting cells share a common progenitor in the avian inner ear. Association between shear stress, angiogene- the aged cochlea of Mongolian gerbils. Glutathione-dependent antioxidant systems changes of intracellular calcium-binding sites after acute noise in the mammalian inner ear: effects of aging, ototoxic drugs and trauma in the organ of Corti of the guinea pig. Requirement for glycogen synthase kinase- oxygen species generation on cochlear function. Proinﬂammatory cytokine expression in the trauma by an iron chelator, a free radical scavenger and glial cell endolymphatic sac during inner ear inﬂammation. Biochem Biophys Res Commun 2000; study of dextran/pentoxifylline medication in acute acoustic trauma 272(2):490–496. Nitric oxide synthase is an active enzyme in the effect of bencyclan in a controlled clinical trial [author’s transl. A role of glutamate in drug-induced ototoxicity: for noise-induced hearing loss: results of a double blind ﬁeld study. Role of nitric oxide in kainic acid-induced ele- Schriftenr Ver Wasser Boden Lufthyg 1993; 88:517–528. Diltiazem for prevention of acoustical trauma dur- Otolaryngol 1998; 118(5):660–665. The protective effects uation of a potential new therapy for severe hearing loss caused ofallopurinol and superoxide dismutase on noise-induced cochlear by inﬂammation. Enhanced preservation of the auditory nerve immune-mediated cochleovestibular disorders: preliminary following cochlear perfusion with nerve growth factors. The site of action of neuronal acidic ﬁbroblast cochleovestibular disorders: a multi-center, open-label, pilot growth factor is the organ of Corti of the rat cochlea. The incidence and management of infusion glial cell line-derived growth factor from degeneration after noise reactions to inﬂiximab: a large center experience. Mol Ther 2003; non-steroidal anti-inﬂammatory agents on the normal and noise- 7(4):484–492. Intratympanic and sys- survival and electrophysiological responsiveness in neomycin- temic dexamethasone for Meniere’s disease. Effects of exposing the opened endolymphatic cells of the organ of Corti: quantitative analysis in developing sac to large doses of steroids to treat intractable Meniere’s disease. Middle ear infu- vival of cultured spiral ganglion neurons and protects them from sion with lidocaine and steroid solution. Transtympanic dexamethasone application in the developing, adult, and regenerating avian cochlea. J Neuro- Meniere’s disease: an alternative treatment for intractable ver- biol 1997; 33(7):1019–1033. Intratympanic dexamethasone, intratym- of neurons in modiolus-spiral ganglion explants. Neuroreport panic gentamicin, and endolymphatic sac surgery for intractable 1995; 6(11):1533–1537. Intratympanic steroid treatment of inner ear the perilymph after local administration vs. Dexamethasone inner ear perfusion for the netics in the inner ear ﬂuids: an animal study followed by clini- treatment of Meniere’s disease: a prospective, randomized, dou- cal application. Treatment of cochlear-tinnitus with inner ear: comparison of route of administration and use of facili- dexamethasone infusion into the tympanic cavity. Effect of ototopic application of a corticos- therapy to inner ear for control of tinnitus. Chronic intrathecal adminis- sudden sensorineural hearing loss after failure of conventional tration of dexamethasone sodium phosphate: pharmacokinetics therapy: a pilot study. J Neurosci 2003; into the round window niche causes electrophysiological dysfunc- 23(24):8596–8607. J Neurochem 2002; 83(4): prostanoid receptors and cyclo-oxygenase enzymes in guinea pig 992–1001. Inﬂuence of aspirin, gentamicin, and acoustic stimu- Cell Biol 1998; 10(2):205–219. J Neurochem 2002; 82(6): latanoprost in Meniere’s disease: a randomized, placebo-con- 1424–1434. The major malformations represent the tics, the frequency of isolated external-ear and external-ear- congenital atresias of the external auditory canal; the minor canal malformations in 1980 amounted to 0. Variable prevalence rates can be due to variable reg- term “congenital atresia of the ear” is generally used to describe istration. A lack of standardisation of deﬁnition and diagnosis a series of malformations of the external and middle ear. Also, substantial variations in the Although atresia anatomically implies an absence of an exter- incidence between different years have been found (4).

Almost half of new cases are diagnosed at an advanced stage order baycip 500 mg with visa, when the 5-year survival rate is just 14 % discount baycip 500mg without prescription. Efforts are being made to evaluate esophageal cancer treatment with a pharmacogenetic-based approach that takes into consideration genes in each drug action pathway as a means of developing a more accurate and consistent risk predic- tion model discount baycip 500 mg free shipping. Patients with resectable adenocarcinoma or squamous cell carcinoma of the esophagus who have been treated with chemoradiation followed by esophagec- tomy show that methylenetetrahydrofolate reductase polymorphisms can modify 5-ﬂuorouracil response. This supports the hypothesis that response or resistance to therapy in esophageal cancer patients may be modulated by genetic variants involved in the metabolism or mechanism of chemotherapy drug action. Further research on esophageal cancer aims to determine individual pharmacogenetic proﬁles to iden- tify patients most likely to have chemotherapeutic beneﬁt and patients with the highest risk of suffering genotoxic side effects. These proﬁles will ideally lead to individualized therapies, improved treatment outcomes, and a movement toward clinically applied pharmacogenetics. This emergent area of biomedicine could lead to substantially improved clinical outcomes for patients with adenocarcinoma or squamous cell carcinoma of the esophagus. The ﬁndings represent a signiﬁcant advance in the goal to provide person- alized therapy because it offers a genetic blueprint for gauging the potential effec- tiveness of all common esophageal cancer treatment, not just an analysis of how one or two “candidate” genes respond to a single treatment. The patients with the best outcomes are those who have gene variants that are less effective at neutralizing the killing power of the cancer treatments. Conversely, patients whose genes efﬁciently counteract chemotherapy and radiation treatment have shorter survival times over- all. Personalized Management of Gastric Cancer Gastric cancer is the second most common cause of cancer death worldwide with approximately one million cases diagnosed annually. Despite considerable improve- ments in surgical techniques, innovations in clinical diagnostics and the develop- ment of new chemotherapy regimens, the clinical outcome for patients with advanced gastric cancer is generally poor with 5-year survival rates ranging between 5 % and 15 %. Universal Free E-Book Store 338 10 Personalized Therapy of Cancer Several molecular therapies are in development for gastric cancer. Osteopontin is a secreted protein involved in stress response, inﬂammation, wound healing, and immune response. Despite the recent results of sys- temic chemotherapy, more than 40 % of patients with advanced cancer still do not achieve substantial beneﬁts with cytotoxic agents. Therefore, personalized strate- gies are warranted to improve the probability of disease control. It is important to have a strategy for screening and early detection for preventive measures. The success of chemotherapy depends on various factors such as gender, age and histological subtype of tumor. These candidates need to be incorporated into large, prospective clinical trials to conﬁrm their impact for response and survival to chemotherapy that has been reported in retrospective anal- yses. Conﬁrmed predictive markers, together with additional yet to be identiﬁed pharmacogenomic key players, will provide the basis for tailoring chemotherapy in the future. The rationale for this approach is based on the identiﬁcation of the in vivo interactions among patient’s characteristics, disease physiopathology, and drug pharmacodynamics and pharmacokinetics. Despite the recent encouraging data, the clinical use of targeted therapy is hampered by several questions that need to be answered such as optimal biologic dose and schedule, lack of predictive surrogate biomarkers, and modalities of combination with chemotherapy/radiotherapy. There is still a need for multiple bio- marker testing and to identify panels of predictive biomarkers in order to improve response rates and decrease toxicity with the ultimate aim of tailoring treatment according to an individual patient and tumor proﬁle. Therefore, an under- standing of these molecular differences is essential for optimizing treatment Universal Free E-Book Store 340 10 Personalized Therapy of Cancer regimens. For this reason the development and application of individualized therapy has been the goal of several studies within the last decade. Bioinformatic analyses identiﬁed sets of genes that were constitutively dysregulated in drug-resistant cells and transiently altered following acute exposure of parental cells to drug. Functional analysis of three genes identiﬁed in the microarray study (prostate-derived factor, calretinin, and spermidine/spermine N1-acetyl transferase) revealed their importance as novel regulators of cytotoxic drug response. Launch of this companion diagnos- tic in 2008 marked the ﬁrst time that the European Commission licensed a bowel cancer treatment with the stipulation that a predictive test should be carried out. Nevertheless, some 15–20 % of these individuals eventually have recurrence of the disease. Therefore, efforts are being made to deﬁne the molecular changes associated with recurrence and decreased survival. Methylation changes associated with mortal- ity may reﬂect genomic instability, transcriptional dysregulation, and the activation of oncogenes, inﬂammation, or oxidative stress. Although follow-up studies are still needed, there are good prospects of clinical application of the results. Another study has identiﬁed a 50-gene signature in early-stage colon cancer that predicts cancer recurrence (Garman et al. The investigators compiled gene expression data from publicly available datasets, assessing the expression patterns in 52 samples taken from individuals with known survival outcomes. Along with its prognostic implications, preliminary results suggest that the signature, which was validated in two independent patient groups, may also provide clues for treating colon cancer. Identiﬁcation of these patients may enable targeted and proactive treatment to prevent this recurrence. The investigators also tested whether the gene signature was useful for guiding individuals’ treatment and identifying new drugs. Using the Broad Institute’s Connectivity Map, they assessed the gene expression proﬁles of cells treated with a range of drugs to look for proﬁles resembling the cancer recurrence signature. Their research suggests that at least four drugs may inﬂuence the genes involved in the recurrence signature. That, in turn, suggests it may be useful to test the treat- ments in those with the high-risk signature in order to identify patients who may beneﬁt from such treatments rather than standard chemotherapy. Additional investigation is needed to validate the clinical relevance of individual genetic differences. Total budget for the project along with funding from the Innovative Medicines Initiative – a private-public partnership between the pharmaceutical industry and the European Union – amounts to €25. The consor- tium, led by Bayer HealthCare Pharmaceuticals and the Max Planck Institute for Molecular Genetics in Germany, includes AstraZeneca, Boehringer Ingelheim, Janssen Pharmaceutica, Merck, Pﬁzer, and Roche Diagnostics. Academic partners include Uppsala University, University College London, Paris South University, Charité Universitätsmedizin Berlin, Medizinische Universität Graz, and Technische Universität Dresden. International Prevention Research Institute, Experimental Pharmacology and Oncology, and Alacris Theranostics also are members of OncoTrack. The data will be compared to the germline genome of the patients, and will be complemented by a detailed molecular characterization of the tumors.