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Are you more about the personality than the stats

Are you more about the personality than the stats

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Are you more about the personality than the stats

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I Want You. I don't want to be married but one time in my life I'm not waiting for my first ex wife. Would be nice to have an attractive, nice lady to spend this coming weekend (or longer) with, Snuggle up and watch some movies, maybe a drive or both.

Goodreads helps you keep track of books you want to read. Want to Read saving…. Want to Read Currently Reading Read. Refresh and try again. Open Preview See a Problem?

Thanks for telling us about the problem. Return to Book Page. What I get instead is stubborn, snarky, wild, lights-my-blood-on-fire Harlow Reed. Harlow is merely looking for nonstop sweaty sex and screaming orgasms that wring pleasure from her oh-so-luscious body.

But the more I know this woman, the less I can picture my life without her. I more than love her enough to do whatever it takes to make her mine for good. Kindle Edition , 1st edition , pages. More Than Words 3. To see what your friends thought of this book, please sign up.

To ask other readers questions about More Than Love You , please sign up. Once Upon September 18, More Than Crave You is on preorder now!

See 1 question about More Than Love You…. Lists with This Book. Feb 16, Natalie The Biblioholic rated it really liked it Shelves: There is so much I can say about this story and my love for all things Noah Told mos There is so much I can say about this story and my love for all things Noah We get to see him find love in all of its intricacies and complications; witness his frustration and elation with every triumph and pitfall in his relationship with Harlow; and while Harlow had the tendency to make me so freaking mad most of the time, I found lots of things about her to like as well.

Usually the greatest rewards come from the harshest of hardships and Noah and Harlow could definitely testify to that. This story was about so much more than a cocky retired NFL quarterback conquering a stubborn woman set against opening her heart to him.

It was more than just about his persistence to win her over, one day at a time. It was more than just sex or feelings or drama or angst. It was about pain, lies, betrayal, deceit, the price of celebrity, bitter heartache, family, and most of all trusting in yourself and in the ones you love.

Primarily Hero - 1st person Heat: View all 18 comments. Noah has just retired from pro football due to some residual effects from the last concussion he received. He's not ready to leave football but he's not sure he can accept the commentary job with the issues he is having.

Harlow found out her fiance was cheating on her with his assistant and has a baby on the way. She breaks off her wedding in the most epic way and needs to hide out for a bit. Noah comes home to his new house he just bought to find a stunning woman sunbathing poolside and finds ou Noah has just retired from pro football due to some residual effects from the last concussion he received.

Noah comes home to his new house he just bought to find a stunning woman sunbathing poolside and finds out she is the house sitter. There is instant chemistry between the two and while Noah sweet talks Harlow into staying the night, he realizes one night isn't going to be enough. This book was such a treat for me. It had all my wishlist items.

My favorite thing to read is where the Hero chases the heroine. I just don't see that enough in romance books. For once, the heroine was the one that was hesitant to commit. While Noah is dealing with his speech issues, Harlow is dealing with some major trust issues that date far back. I do think she pushes a bit too much, but I don't even care because it just showed how much Noah loved and wanted Harlow in his life. This was just what I was looking for! View all 16 comments. I hope you fall in love with Noah and Harlow as much as I have!

Download your copy today! I voluntarily reviewed an Advance Reader Copy of the book. Noah Weston was unlike any other male lead I've read, especially considering he's a retired quarterback not that I subscribe to any particular stereotype about athletes.

He was so open and in touch with his feelings and so willing to risk so much for the chance of something great. The way he fell for poor Harlow and the way he fought for her and her heart and peace and future was just beautiful. And Harlow - she was strong in the way that only broken things can be. This book was so wonderfully written and I really enjoyed the fact that it's predominantly told from Noah's first person POV.

It also contained one of my favorite kinds of angst - that that comes with evil family members! I'm hoping that some of the developments revealed in this book lead to more books in the series - the Reed siblings are a tough and lovable bunch and I'd love to read more about them. I do recommend reading the first two books beforehand to understand the Reed family dynamic and get to know the characters that make appearances.

Scandal has both Noah Weston and Harlow Reed hiding out at a private ocean-front property. Neither is looking for a relationship, but they decide to use their passion and attraction to present themselves as a supportive and loving couple until the scandals pass over.

But what happens when the ruse is over, and they realize it more? This book has the roles reversed. The male character is usually the one shying away from love, but not Noah. No once he realizes what he feels, he then makes it his mission to convince Harlow that she feels the same.

But he has a hard road ahead of him with that. She has built the walls surrounding her heart high. But if anyone can break them down or find a way over them its Noah. It was like visiting family and catching up a bit. Shayla has written another fully captivating book within this series. As always, I loved it and I cannot wait to see what she gives me next. More Than Love You is a fun, scorching-hot romance with a layered, powerful love story.

Noah Weston is a recently retired football player with a big personality who meets his match with the feisty, complicated Harlow Reed. Their chemistry is instant, and their relationship begins as a fiery physical one.

But Harlow just excited a relationship in an ext More Than Love You is a fun, scorching-hot romance with a layered, powerful love story. They agree to embark on a fake relationship in order to help both of their reputations in the public eye, but the line between pretend romance and real feelings quickly blurs. Noah realizes he wants forever with Harlow, and he commits himself to winning her with all the fierceness expected of a former professional athlete.

Readers will fall hard for Noah, a brash jock with a tender heart. Their love story begins as an explosion of steamy sex, but their relationship evolves with a genuineness that makes it satisfying and perfectly romantic. More Than Love You had me laughing, swooning, tearing up and blushing. ARC provided, but this review was voluntarily and honestly written.

May 08, Angel Payne rated it it was amazing. This series is Ms. Black at her best, and just keeps getting better and better! This one tore my heart out in so many ways.

So many feels and wonderful, heartfelt tears. Feb 19, Kathleen R. Feb 16, Rebecca rated it it was amazing. There are a lot of personal issues that Noah and Harlow must sift through in order for the feelings they have for each other to grow into something more. Noah needs to deal with the end of his Pro Football career and the health complications that have posed a road block for his second career opportunity.

Harlow is a bit of a wild card for a number of reasons; every time Noah pushes too much, she shuts down and uses humor or sex to evade any emotional discussions. Noah decides to return t "I don't know how to not touch Harlow. Noah decides to return to Hawaii, where he grew up when he retires from his career as a quarterback for the NFL. Having a successful football career for the last decade allowed him to retire in style in his dream home right on the ocean.

The remote location also gives him a break from the media attention that is relentless. He bought the home sight unseen, insisting that it be ready for him to move in immediately when he arrived. What he wasn't expecting when he got there was the beauty in a red bikini lounging next to his pool. He didn't know why she was there, but he wanted to keep her I was very amused by the fact that she had no clue who he was, and was not impressed by his celebrity.

However, she did perk up when she realized he owned the home that she was housesitting, and that made him her boss. She was ready to pack her bags and leave him to it, but that was the last thing he wanted.

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One can learn a great deal by using the help windows, but if they are available, it is better to study the package vignette. Package vignettes All packages have help pages for each function in the package. These are meant to help you use a function that you already know about, but not to introduce you to new functions. An increasing number of packages have a package vignettes that give more of an overview of the program than a detailed description of any one function. These vignettes are accessible from the help window and sometimes as part of the help index for the program.

The two vignettes for the psych package are also available from the personality project web page. An overview of the psych package and Using the psych package as a front end to the sem package.

Commands are entered into the "R Console" window. You can add a comment to any line by using a. The Mac version has a text editor window that allows you to write, edit and save your commands. Alternatively, if you use a normal text editor As a Mac user, I use BBEDIT, PC users can use Notepad , you can write out the commands you want to run, comment them so that you can remember what they do the next time you run a similar analysis, and then copy and paste into the R console.

Although being syntax driven seems a throwback to an old, pre Graphical User Interface type command structure, it is very powerful for doing production statistics. Once you get a particular set of commands to work on one data file, you can change the name of the data file and run the entire sequence again on the new data set. This is is also very helpful when doing professional graphics for papers. In addition, for teaching, it is possible to prepare a web page of instructional commands that students can then cut and paste into R to see for themselves how things work.

That is what may be done with the instructions on this page. It is also possible to write text in latex with embedded R commands. Then executing the Sweave function on that text file will add the R output to the latex file.

This almost magical feature allows rapid integration of content with statistical techniques. More importantly, it allows for "reproducible research" in that the actual data files and instructions may be specified for all to see. As you become more adept in using R, you will be tempted to enter commands directly into the console window.

I think it is better to keep annotated copies of your commands to help you next time. Command syntax tends to be of the form: Not necessary, but useful. Help and Guidance For a list of all the commands that use a particular word, use the apropos command: A very nice example is demo graphics which shows many of the complex graphics that are possible to do.

Back to Top There are multiple ways of reading data into R. From a text file For very small data sets, the data can be directly entered into R. For more typical data sets, it useful to use a simple text editor or a spreadsheet program e. You can enter data in a tab delimted form with one variable per column and columns labeled with unique name.

A numeric missing value code say is more convenient than using ". To read the data into a rows subjects by columns variables matrix use the read. A very useful command, for those using a GUI is file. In this case, you can specify that the seperators are commas. From the web For teaching, it is important to note that it is possible to have the file be a remote file read through the web.

Note that for some commands, there is an important difference between line feeds and carriage returns. For those who use Macs as web servers, make sure that the unix line feed is used rather than old Mac format carriage returns.

For simplicity in my examples I have separated the name of the file to be read from the read. These two commands can be combined into one. The file can be local on your hard disk or remote.

For most data analysis, rather than manually enter the data into R , it is probably more convenient to use a spreadsheet e. Most of the examples in this tutorial assume that the data have been entered this way. Many of the examples in the help menus have small data sets entered using the c command or created on the fly.

The file is structured normally, i. To read from a local file, we simply change the name of the datafilename. Tables allow one to have columns that are either numeric or alphanumeric. To address a particular row e. In order to select a particular subset of the data, use the subset function.

The next example uses subset to display cases where the lie scale was pretty high subset person. Use the package manager option package. I will check this. If files are saved on remote servers, use the load url remoteURLname command. Commands are entered in the command console and at least for Macs , are colored red while results in the results console are shown in blue.

Commands can be cut and pasted from a text editor or from a browser if following along with examples into the command console. Like Unix or OS X, using the up arrow shows previous commands. It is a useful habit to be consistent in your own naming conventions. Some use lower case letters for variables, Capitalized for data frames, all caps for functions, etc. It is easier to edit your code if you are reasonably consistent. Comment your code as well.

This is not just so others can use it, but so that you can remember what you did 6 months later. The with construct is more appropriate when doing some specific analysis. Yet another way to call elements of a variable is to address them directly, either by name or by location: Two of the most useful are the ability to replace if a certain condition holds, and to find subsets of the data.

Consider the problem of scoring a multiple choice test where we are interested in the number of items correct for each person. Define a scoring key vector and then score as 1 each item match with that key. Then find the number of 1s for each subject. We use the Iris data set as an example. Actually, to score a multiple choice test, use score. Basic descriptive statistics Back to Top ls list the variables in the work space ls [1] "bfi.

Median Mean 3rd Qu. However, there is a very useful command scale that does this automatically epiz Compare the two results. In the first, all the means are 0 and the sds are all 1.

The second also has been centered, but the standard deviations remain as they were. This next example also introduces the apply function which applies a particular function to the rows or columns of a matrix or data. Although the summary function gives Tukey's 5 number summaries, many psychologists will find the describe function in the psych more useful.

For those who are more accustomed to testing many correlations, corr. Back to Top A quick overview of some of the graphic facilities. For a stunning set of graphics produced with R and the code for drawing them, see addicted to R: Enhance your data visualisation with R. A more complete listing and discussion of these examples including the output is in the R. This section just gives example instructions. The example data set is stored at the personality-project. One way repeated Measures Repeated measures are some what more complicated.

However, Jason French has prepared a very useful tutorial on using R for repeated measures. This is not a typical way to enter data. A more typical way found e. We need to "stack" the data to go from the standard input to the form preferred by the analysis of variance. Consider the following analyses of 27 subjects doing a memory study of the effect on recall of two presentation rates and two recall intervals. Each subject has two replications per condition. The first 8 columns are the raw data, the last 4 columns collapse across replications.

The data are found in a file on the personality project server. We then need to create a new data. This seems more complicated than it really is although it is fact somewhat tricky. It is useful to list the data after the data frame operation to make sure that we did it correctly.

This and the next two examples are adapted from Baron and Li's page. We make use of the rep , c , and factor functions. Generalizations of the linear model include an even wider range of statistical models. Consider the following models: These models can be fitted with the linear model function lm and then various summary statistics are available of the fit.

The data set is our familiar set of Eysenck Personality Inventory and Big Five Inventory scales with Beck Depression and state and trait anxiety scales as well. Note that we need to 0 center the predictors when we have an interaction term if we expect to interpret the additive effects correctly.

Centering is done with the scale function. Graphical summaries of the regession show four plots: Models 5 and 6 predict bdi using the BFI, and model 7 for too much fitting looks at the epi and bfi and the interactions of their scales. What follows are the commands for a number of demonstrations. Samples of the commands and the output may be found in the regression page. Further examples show how to find regressions for multiple dependent variables or to find the regression weights from the correlation matrix rather than the raw data.

In order to visualize interactions, it is useful to plot regression lines separately for different groups. This is demonstrated in some detail in a real example based upon heating demands of two houses. Back to Top Scale Construction and Reliability This section, written fours years ago, shows how to do the analyses in "vanilla R".

I recommend installing the psych package from CRAN and using the more powerful functions in that pacakge. One of the most common problems in personality research is to combine a set of items into a scale. Questions to ask of these items and the resulting scale are a what are the item means and variances. For a somewhat longer discussion of this, see the internal structure of tests.

The following steps analyze a small subset of the data of a large project the synthetic aperture personality measurement project at the Personality, Motivation, and Cognition lab.

The data represent responses to five items sampled from items measuring extraversion, emotional stability, agreeableness, conscientiousness, and openness taken from the IPIP International Personality Item Pool for subjects. Since there were two reversed items, this is the same as adding 14 E1. Some items were negatively correlated with total scale and were automatically reversed Scoring multiple choice tests If you are using multiple choice tests and want to score the items following a key, it is possible to use the power of R for data manipulation: A more typical example using the score.

Install R on your computer or go to a machine that has it. Download the psych package as well as other recommended packages from CRAN using the install. To get packages recommended for a particular research field, use the ctv package to install a particular task view. Note, these first two steps need to be done only once!

Activate the psych package or other desired packages using e. This needs to be done every time you start R. Or, it is possible to modify the startup parameters for R so that certain libraries are loaded automatically. Enter your data using a text editor and save as a text file perhaps comma delimited if using a spreadsheet program such as Excel or OpenOffice Read the data file or copy and paste from the clipboard using, e.

Find basic descriptive statistics e. Prepare a simple descriptive graph e. Find the correlation matrix to give an overview of relationships if the number is not too great, a scatter plot matrix or SPLOM plot is very useful, this can be done with pairs. If you have an experimental variable, do the appropriate multiple regression using standardized or at least zero centered scores.

If you want to do a factor analysis or principal components analysis, use the fa or principal functions. To score items and create a scale and find various reliability estimates, use score. Installing R on your computer Although it is possible that your local computer lab already has R, it is most useful to do analyses on your own machine. For the following analyses, we will use data from the Motivational State Questionnaire MSQ collected in several studies.

Are happiness and sadness truly opposite affects? Motivation and Emotion, 30, 1, This clearly saves computational time for large data sets. This matrix can be saved and then reloaded.

The similarity of the three different solutions may be found by using the factor. Routines for the Very Simple Structure VSS criterion allow one to compare solutions of varying complexity and for different number of factors. Alternatives include the scree test. To use these routines on a data set with items, myitems,: General Factor Saturation of a test McDonald has proposed coefficient omega as an estimate of the general factor saturation of a test.

They conclude that omega is the best estimate. See also Zinbarg et al. Here we present code to do that. This code is included in the psych package of routines for personality research that may be loaded from the CRAN repository or, for the the recent development version, from the local repository at http: General Factor Saturation of a test Beta, an alternative to omega, is defined as the worst split half reliability. It can be estimated by using ICLUST Revelle, , a hierarchical clustering algorithm originally developed for main frames and written in Fortran and that is now part of the psych package.

What took multiple years and about lines of code in Fortrantook about 4 days and lines of R. Factor rotations Rotations available in the basic R installation are Varimax and Promax. A powerful additional set of oblique transformations including Oblimin, Oblimax, etc. Using this package, it is also possible to do a Schmid Leiman transformation of a hierarchical factor structure to estimate the general factor loadings and general factor saturation of a test.

Cluster Analysis A common data reduction technique is to cluster cases subjects. Less common, but particularly useful in psychological research, is to cluster items variables. This may be thought of as an alternative to factor analysis, based upon a much simpler model.

The cluster model is that the correlations between variables reflect that each item loads on at most one cluster, and that items that load on those clusters correlate as a function of their respective loadings on that cluster and items that define different clusters correlate as a function of their respective cluster loadings and the intercluster correlations.

Essentially, the cluster model is a factor model of complexity one see VSS. An example of clustering variables can be seen using the ICLUST algorithm to the 24 tests of mental ability of Harman and then using the Graphviz program to show the results.

Consider the distances between nine American cities. Can we represent these cities in a two dimensional space. See the pages on multidimensional scaling and Thurstonian scaling. See his page at http: The sem package, developed by John Fox, the lavaan package by Yves Rosseel, and the OpenMx package by Steve Bolker allow for most structural equation models.

To use then, add the sem , lavaan or OpenMx packages. Structural Equation Modeling may be thought of as regression corrected for attentuation. Fox has prepared a brief description of SEM techniques as an appendix to his statistics text. When morning types played in early games with start times before 2 p. But when evening types played in night games with first pitch after 8 p. A number of studies support these connections.

One analysis of adults from a Finnish twin cohort found that evening types were much more likely to be current or lifelong smokers, much less likely to stop smoking, and at much higher risk for nicotine dependence as per diagnostic criteria, compared with morning folks.

Another study of individuals found that owls consume more alcohol than larks. In a paper notable for focusing on adolescents, Randler and a Heidelberg colleague discovered a link between night people and novelty-seeking already present among German teenagers technically, ages 12 to These positive traits among morning types built on other personality work from Randler showing that larks tended to be more agreeable and conscientious , and that they tend to be more proactive than owls.

Given that larks are generally more compliant and conformist than owls, it comes as little shock to learn that evening types seem to be worse procrastinators. Based on six days of daily task records, Ferrari and company linked procrastination behaviors with a general tendency to partake in evening activities. That study focused on college students: But the finding held true in a study of an adult sample with a mean age of Once again, being a night owl was associated with avoiding a task that needed to be completed, the study team which included Ferrari reported in the Journal of General Psychology.

The researchers also suspect that this general preference to delay tasks until night could create problems at jobs with strong daytime work expectations. This disconnect between conventional daytime expectations and nighttime preference might make life harder for owls in general. They might also be less happy as a result. After assessing a sample of young adults 17 to 38 and older adults 59 to 79 on their chronotypes as well as their current moods, the researchers found that morning people had higher positive affect across the board, compared with night people.

It might even brew some creativity, according to a study by psychologists Mareike Wieth and Rose Zacks. Wieth and Zacks determined the chronotype of test participants then randomly assigned them to a morning or late afternoon test session. During the session, the participants had to solve six problems.

Brief pause for an example insight problem: An antique coin dealer gets an offer to buy a bronze coin with the date B. No coin truly made in B. In the journal Thinking and Reasoning , Wieth and Zacks report that, overall, people were more successful at the analytical problems. But participants had a higher solution rate for insight problems when doing them at their non-optimal time of the day—say, an owl doing the test in morning—than at the time that aligned with their chornotype.

The results lend support to the incubation theory of creativity: By Eric Jaffe 9 minute Read. Andre Valadao via Shutterstock. If anything, owls might be a bit smarter on the whole. Flickr user Kristina Servant. No, literally, they play baseball better.

Search the world's information, including webpages, images, videos and more. Google has many special features to help you find exactly what you're looking for. Tolerance is inevitable with caffeine, can’t help you there. But anxiety and jitteriness are not: try taking L-theanine with your caffeine. It’s a compound found in tea, is available over the counter (in the US, at least), and is an effective anxiolytic, promoting calm focus alongside the caffeine’s energy. More on the psych package. The psych package is a work in progress. The current released version is Updates are added sporadically, but usually at least once a quarter. The development version is always available at the pmc repository.. If you want to help us develop our understanding of personality, please take our test at SAPA Project. ©William Revelle and the Personality .