|
AN_St1 * HA_St1 Crosstabulation |
||||
|
Count |
||||
|
|
HA_St1 |
Total |
||
|
0 |
1 |
|||
|
AN_St1 |
0 |
2942 |
29 |
2971 |
|
1 |
26 |
1 |
27 |
|
|
2 |
2 |
0 |
2 |
|
|
Total |
2970 |
30 |
3000 |
|
|
Chi-Square Tests |
|||
|
|
Value |
df |
Asymptotic Significance (2-sided) |
|
Pearson Chi-Square |
2.031a |
2 |
.362 |
|
Likelihood Ratio |
1.236 |
2 |
.539 |
|
Linear-by-Linear Association |
1.386 |
1 |
.239 |
|
N of Valid Cases |
3000 |
|
|
|
a. 3 cells (50.0%) have expected count less than 5. The minimum expected count is .02. |
|||
|
Directional Measures |
||||||
|
|
Value |
Asymptotic Standardized Errora |
Approximate Tb |
Approximate Significance |
||
|
Ordinal by Ordinal |
Somers' d |
Symmetric |
.024 |
.033 |
.722 |
.470 |
|
AN_St1 Dependent |
.024 |
.033 |
.722 |
.470 |
||
|
HA_St1 Dependent |
.025 |
.034 |
.722 |
.470 |
||
|
a. Not assuming the null hypothesis. |
||||||
|
b. Using the asymptotic standard error assuming the null hypothesis. |
||||||
I’ll say Yes and No.
The within kid crosstabs will summarize the four outcomes and you could report the percentages for each outcome for each kid. The key word is “summarize”. (That’s the Yes part). Of course, you can compute a chi-square value or a phi correlation but the chi square and phi significance test is based on the observations being independent. Yours are not. (That’s the No part). If summarizing is acceptable to your committee; then, you’re done. That’s the key question.
I want to point out that within your dataset, you can make up many different relationships to summarize. Right now, you are focusing on the percentage of observations in which AN and HA both occurred at a given time point.
Gene Maguin
From: Michael Bates <[hidden email]>
Sent: Monday, March 12, 2018 12:33 PM
To: Maguin, Eugene <[hidden email]>
Cc: [hidden email]
Subject: Re: 2 Variables, 7 cases, 10 observations -- Simple?
That's exactly right. It was #,# for 3000 data points per kid. Most were 0,0, In fact, I found 1074 individual seconds where one kids or another exhibited anxiety and fewer seconds of hyperactivity for any given child.
My data files are as you describe:
KidID Time AN HA
You're saying I can create individual data sets for each child and run a cross tab AN by HA. It wouldn't matter about normal curve or not in that case, I could scrap the correlation metrics completely and rely on the cross tab alone. I would have to then describe the results by child in my results/discussion sections rather than having a statistic for overall relationship between variables, though my discussion would make that general statement based on the cross tabs. Have I got all that right?
On Mon, Mar 12, 2018 at 11:13 AM, Maguin, Eugene <[hidden email]> wrote:
Ok, that’s very helpful, I think. So, at any given second there can be four code pairs (AN, HA): (0,0); (0,1); (1,0); (1,1). Except for kids leaving the setting, there would be 3000 (50*60) records per kid; although many or even all records might be (0,0) for a given kid. I understand that it is extremely likely that your data is not in this form but if your data records were Kidid, observation, Anx, HA, where observation equals time coded in seconds, you could split the file by kidid and crosstab Anx by HA.
Gene Maguin
From: Michael Bates <[hidden email]>
Sent: Monday, March 12, 2018 11:42 AM
To: Maguin, Eugene <[hidden email]>
Cc: [hidden email]
Subject: Re: 2 Variables, 7 cases, 10 observations -- Simple?
The raters (more than one for inter-rater reliability reasons) observed videos of children in a classroom setting for 50 minutes. Coding tracked defined anxiety behavior and defined hyperactivity behavior. The coders had coding sheets that had columns for Time (in seconds), AN and HA. They put a tally "1" in the variable column at the noted second if either of the behaviors was observed. So, for a given subject, the coding sheet had:
Time AN HA
00:00:00 1 1
00:00:01 1
00:00:02 1
...etc
The tallies of both variables were totaled. In addition to the individual observations, time was aggregated in 5 minute blocks. If the child left the observation session (doctor's appointment, nurse's office, whatever), the totals for a given 5 minute block ended up totaled as 0. Each 5 minute aggregate was labeled T1, T2, etc. Only 7 children agreed to participate. Don't get me started....
My first research question related to the the amount of anxiety and hyperactivity: Do highly anxious children exhibit a higher level of HA than low anxiety children? Originally, I thought to run frequencies/correlations on the second-by-second data for each student. Then I thought to run the 5 minute block aggregates. I found that my data to be non-normalized, and I decided that Pearson's r was not appropriate to determine the correlation between the two variables. I ran a scatter plot to determine monotonicity and found an adequate relationship. So, I ran Spearman and Kendall on the 5 minute blocks, then Somers (because of the IV/DV nature of the data). I found a strong positive correlation in each output. As the comments came back from the SPSSX Extremely! helpful responders, I understood that my data might be overstated and I ran the same procedures on the means. This yielded no significant correlation in either direction. (Poop! Technical term?)
Another research question related to the "causal" relationship between AN and HA. So, I coded any HA that followed withing 30 seconds of an AN observation (a theoretically defensible time frame) to indicate that for that pair of observations, HA followed from AN. This I ran as the total of AN against the total HA within 30 seconds of AN by student (of the total AN observed for each student, how many were followed within 30 seconds by HA?). Interestingly,I found a strong positive relationship between the variables.
That's the set up, in a nutshell.
On Mon, Mar 12, 2018 at 9:13 AM, Maguin, Eugene <[hidden email]> wrote:
I'd like to better understand your study design (I've re-read the initial round of posts.) In your reply, you said, you observed the target kid for a total of 50 minutes. What I'm curious about is the data collection procedures used. I think these matter in understanding what your data analysis options are. The target behaviors were anxiety (Anx) and hyperactivity (HA). For example, you could have tabulated using two hand counters or hash-marks on paper each time a target behavior occurred so that at any point in time, the HA counter or hash count would show a count of 15 and the Anx counter or hash count would show a count of 8. Alternatively, you could have recorded in a data sequence the behaviors as they occurred so now the recording sheet/data recorder shows, for example, A,H,H,A,A,H,H,H. Alternatively, you could have designated HA as the stimulus behavior and Anx as the response behavior and coded (HA,Anx) if Anx followed HA within 'x' seconds; otherwise, coded (HA,NoAnx). In one of your replies, you mentioned something about 30 seconds. What's the story with that?
Gene Maguin
-----Original Message-----
From: SPSSX(r) Discussion <[hidden email]> On Behalf Of PsyDStats
Sent: Sunday, March 11, 2018 2:47 PM
To: [hidden email]
Subject: Re: 2 Variables, 7 cases, 10 observations -- Simple?
Okay, so I've dabbled a little and successfully confused myself even more.
Let me boil things down.
As I mentioned, I am interested to know if there's a correlation between Anxiety (AN) and Hyperactivity (HA). Does HA go up when AN goes up? Aside from being a very small N, the data also are not normally distributed, so I've been working with nonparametric measures.
Based on the suggestions so far, I ran the means for each student for the two variables. I re-ran the Spearman, Kendall's, and Somer's and found that there was a very poor correlation between AN and HA.
I structured the data:
Mean_AN Mean_HA
St_1 10.33 10.00
St_2 28.67 14.83
St_3 26.17 16.67
St_4 25.10 26.30
St_5 20.50 22.30
St_6 41.50 25.70
St_7 31.75 30.50
If there were no data points missing (those pesky 0's in my data set), and if the N was more substantial, and if I had only kept up with my piano lessons as a kid and I were now conducting at the Met instead of a doctoral student in psychology, would you say that I've chosen the correct measures for my data set and structured it properly in SPSS? Would you say that there is a chance the outcomes of the procedures I've run are useful to me in accepting or rejecting the Null Hypothesis, which in this case is that I should go back to piano (My mother's null hypothesis that I would amount to Null if I gave up the piano)?
Seriously, thanks for your thoughtful feedback.
--
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