What is the difference between NP and DNP?

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I was looking into future possibilities through Arizona State University and noticed that all their NP programs are "DNP". Does this mean you get the title of Dr. once you get this degree vs the NP degrees?

I have a long ways to go, but I can't find the answer to this anywhere and it's confusing.

Thanks,

Amber

Power (1- beta) is a measure of the number of subjects. Not having enough power for every measure means that there were differences approaching statistical significance (like the p=0.12), but there were not enough subjects. Had they enrolled more subjects, it would have been statistically significant. Even in this small study the power was sufficient on 3 measures to indicate statistical significance.

The implication is that despite the fact that NPs claim to save money for the system by having lower reimbursements, there are hidden costs there from shifting the burden onto a specialist doc or by ordering more tests.

There is no implication because the sample is not large enough to be statistically valid. The interpretation of the results says nothing about the tests being unecessary. You are using flawed logic to draw a conclusion that there are any hidden costs in independent practice for nurse practitioners.

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I was taught (by a member of the Harvard medical faculty :) ) that you shouldn't consider any study with fewer than 100 participants to be meaningful.

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I was taught (by a member of the Harvard medical faculty :) ) that you shouldn't consider any study with fewer than 100 participants to be meaningful.

I guess they don't teach such things in medical school. Seems as though our friend wowza has been taught in medical school that as long as you like the results, having a stasticially invalid sample is okay.

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I was taught (by a member of the Harvard medical faculty :) ) that you shouldn't consider any study with fewer than 100 participants to be meaningful.

Well its good there were 450 participants in that study.

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Well its good there were 450 participants in that study.

Laughable. There were only 9 nurse practitioners, isn't that who you are trying to draw conclusions about? Why don't you go ahead and just admit that you haven't a shred of evidence to prove your point. Don't post ridiculous drivel with no evidence, please.

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Laughable. There were only 9 nurse practitioners, isn't that who you are trying to draw conclusions about? Why don't you go ahead and just admit that you haven't a shred of evidence to prove your point. Don't post ridiculous drivel with no evidence, please.

Pretty experienced NPs though (avg. 13 yrs). I find it funny that you're telling wowza that he hasn't a shred of evidence to prove his point when people on these boards clearly refuse to understand that there is no shred of evidence suggesting NPs/DNPs provide equivalent care as board-certified physicians.

I guess they don't teach such things in medical school. Seems as though our friend wowza has been taught in medical school that as long as you like the results, having a stasticially invalid sample is okay.

Actually, that's more like what the nursing community does. Citing hugely flawed studies that say patient satisfaction = good medical outcome, measuring (randomly) diastolic at the end of a study w/o measuring it at the beginning and then using that measure to make an inference, etc. Look through the threads on these forums. These same studies are cited repeatedly. Maybe you guys need even more stats courses than you already have. Or maybe you're consciously citing bad studies because they falsely put you in good light. I'm not sure which it is.

Also, reread what wowza wrote regarding power. What he/she said is actually true. Even with a small sample size the power was pretty significant...which means it'll be even more significant with a larger sample. Here, I'll quote from "An Introduction to Statistical Methods and Data Analysis," Fifth Edition, R. Lyman Ott in case you continue to refuse to believe us or toss more insults our way:

"The larger the sample size n, the more information we have concerning mu, the less likely we are to make a Type II error, and, hence, the smaller the value of beta." (pg. 218)

So, what wowza says is correct. A larger sample size will increase the power of the test, which would make the results even more significant. Refresh your stats knowledge.

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Pretty experienced NPs though (avg. 13 yrs). I find it funny that you're telling wowza that he hasn't a shred of evidence to prove his point when people on these boards clearly refuse to understand that there is no shred of evidence suggesting NPs/DNPs provide equivalent care as board-certified physicians.

Actually, that's more like what the nursing community does. Citing hugely flawed studies that say patient satisfaction = good medical outcome, measuring (randomly) diastolic at the end of a study w/o measuring it at the beginning and then using that measure to make an inference, etc. Look through the threads on these forums. These same studies are cited repeatedly. Maybe you guys need even more stats courses than you already have. Or maybe you're consciously citing bad studies because they falsely put you in good light. I'm not sure which it is.

Also, reread what wowza wrote regarding power. What he/she said is actually true. Even with a small sample size the power was pretty significant...which means it'll be even more significant with a larger sample. Here, I'll quote from "An Introduction to Statistical Methods and Data Analysis," Fifth Edition, R. Lyman Ott in case you continue to refuse to believe us or toss more insults our way:

"The larger the sample size n, the more information we have concerning mu, the less likely we are to make a Type II error, and, hence, the smaller the value of beta." (pg. 218)

So, what wowza says is correct. A larger sample size will increase the power of the test, which would make the results even more significant. Refresh your stats knowledge.

I never insluted anyone. You are the one who is hurling the insults here. You are making the assumption that you will find the same results in the larger sample size, but you know what assuming makes you. So what wowza says is garbage still. YOU can now be lumped with wowza as a statistical novice. You seem to be able to read the book, but you can't understand what it says. Maybe some reading comprehension skills would help all of those med students out there.

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Laughable. There were only 9 nurse practitioners, isn't that who you are trying to draw conclusions about? Why don't you go ahead and just admit that you haven't a shred of evidence to prove your point. Don't post ridiculous drivel with no evidence, please.

Pretty experienced NPs though (avg. 13 yrs). I find it funny that you're telling wowza that he hasn't a shred of evidence to prove his point when people on these boards clearly refuse to understand that there is no shred of evidence suggesting NPs/DNPs provide equivalent care as board-certified physicians.

I guess they don't teach such things in medical school. Seems as though our friend wowza has been taught in medical school that as long as you like the results, having a stasticially invalid sample is okay.

Actually, that's more like what the nursing community does. Citing hugely flawed studies that say patient satisfaction = good medical outcome, measuring (randomly) diastolic at the end of a study w/o measuring it at the beginning and then using that measure to make an inference, etc. Look through the threads on these forums. These same studies are cited repeatedly. Maybe you guys need even more stats courses than you already have. Or maybe you're consciously citing bad studies because they falsely put you in good light. I'm not sure which it is.

Also, reread what wowza wrote regarding power. What he/she said is actually true. Even with a small sample size the power was pretty significant...which means it'll be even more significant with a larger sample. Here, I'll quote from "An Introduction to Statistical Methods and Data Analysis," Fifth Edition, R. Lyman Ott:

"The larger the sample size n, the more information we have concerning mu, the less likely we are to make a Type II error, and, hence, the smaller the value of beta." (pg. 218)

So, what wowza says is correct. A larger sample size will increase the power of the test, which would make the results even more significant. Refresh your stats knowledge.

Up Vote Up Vote ×

I never insluted anyone. You are the one who is hurling the insults here. You are making the assumption that you will find the same results in the larger sample size, but you know what assuming makes you. So what wowza says is garbage still. YOU can now be lumped with wowza as a statistical novice. You seem to be able to read the book, but you can't understand what it says. Maybe some reading comprehension skills would help all of those med students out there.

Up Vote Up Vote ×
I never insluted anyone. You are the one who is hurling the insults here. You are making the assumption that you will find the same results in the larger sample size, but you know what assuming makes you. So what wowza says is garbage still. YOU can now be lumped with wowza as a statistical novice. You seem to be able to read the book, but you can't understand what it says. Maybe some reading comprehension skills would help all of those med students out there.

Haha, you never insulted anyone? What about the repeat attacks on med students' critical thinking skills, the snide remarks suggesting med schools don't teach you things, attacking "reading comprehension skills" (in the post I'm quoting itself), etc? Don't forget your statement that med schools "teach you to cry about student loans, whine about how low your pay is, and then beg society to give you more money." You're absolutely right, no insults thrown at all!

If the chance of failing to reject a false null hypothesis is small in a small study, it's very likely it'll be even smaller in a larger study. Why wouldn't you see similar results when using more NPs? They're already using pretty experienced ones and saw significance. Adding more would just increase the power.

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Haha, you never insulted anyone? What about the repeat attacks on med students' critical thinking skills, the snide remarks suggesting med schools don't teach you things, attacking "reading comprehension skills" (in the post I'm quoting itself), etc? Don't forget your statement that med schools "teach you to cry about student loans, whine about how low your pay is, and then beg society to give you more money." You're absolutely right, no insults thrown at all!

If the chance of failing to reject a false null hypothesis is small in a small study, it's very likely it'll be even smaller in a larger study. Why wouldn't you see similar results when using more NPs? They're already using pretty experienced ones and saw significance. Adding more would just increase the power.

Those aren't insults, those are just the facts. They do cry, they don't comprehend, and they don't think. It is obvious that you subscribe to the teaching as you aren't able to think critically about this study. You can't extrapolate to a population if you don't have a representative sample.

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Those aren't insults, those are just the facts. They do cry, they don't comprehend, and they don't think. It is obvious that you subscribe to the teaching as you aren't able to think critically about this study. You can't extrapolate to a population if you don't have a representative sample.

Facts? Haha. You crack me up with your ignorant statements. You mean like nurses cry about physician egos, physician incomes, physicians standing in their way to complete takeover of medicine, etc? You mean like how nurses can't comprehend how little of medicine they know but still want to practice independently? You mean like you guys can't think when it comes to furthering Mundinger's BS and pretending to be physicians? If so, sure I guess you can call it crying.

I also find it funny that you're extrapolating to a population (med students) based on what a few posters have written (of which, only one is a med student, wowza) while telling me that you can't extrapolate to a population without a representative sample. Hypocrisy, thy name is you. How can I trust that you know stats when you make such blatantly ignorant statements?

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